| 文件 | 最后提交记录 | 最后更新时间 |
|---|---|---|
[mlir][SCF] scf.parallel: Make reductions part of the terminator (#75314) This commit makes reductions part of the terminator. Instead of scf.yield, scf.reduce now terminates the body of scf.parallel ops. scf.reduce may contain an arbitrary number of reductions, with one region per reduction. Example: mlir %init = arith.constant 0.0 : f32 %r:2 = scf.parallel (%iv) = (%lb) to (%ub) step (%step) init (%init, %init) -> f32, f32 { %elem_to_reduce1 = load %buffer1[%iv] : memref<100xf32> %elem_to_reduce2 = load %buffer2[%iv] : memref<100xf32> scf.reduce(%elem_to_reduce1, %elem_to_reduce2 : f32, f32) { ^bb0(%lhs : f32, %rhs: f32): %res = arith.addf %lhs, %rhs : f32 scf.reduce.return %res : f32 }, { ^bb0(%lhs : f32, %rhs: f32): %res = arith.mulf %lhs, %rhs : f32 scf.reduce.return %res : f32 } } scf.reduce operations can no longer be interleaved with other ops in the body of scf.parallel. This simplifies the op and makes it possible to assign the RecursiveMemoryEffects trait to scf.reduce. (This was not possible before because the op was not a terminator, causing the op to be DCE'd.) | 2 年前 | |
[mlir][bufferization][NFC] Rename to_memref to to_buffer (#137180) As part of the work on transitioning bufferization dialect, ops, and associated logic to operate on newly added type interfaces (see 00eaff3e9c897c263a879416d0f151d7ca7eeaff), rename the bufferization.to_memref to highlight the generic nature of the op. Bufferization process produces buffers while memref is a builtin type rather than a generic term. Preserve the current API (to_buffer still produces a memref), however, as the new type interfaces are not used yet. | 1 年前 | |
Adding to execute_region_op some missing support (#164159) Adding canonicalization pattern in case execute_region op has yieldOps which operands are from outside the execute_region, then it simplifies the op to return just internal values. The pattern is applied only in case all yieldOps within execute_region_op have same operands --------- Co-authored-by: Mehdi Amini <joker.eph@gmail.com> | 9 个月前 | |
[mlir][NFC] Update remaining textual references of un-namespaced func operations The special case parsing of operations in the func dialect is being removed, and operations will require the dialect namespace prefix. | 4 年前 | |
[mlir][SCF] Add folding for IndexSwitchOp (#70924) | 2 年前 | |
[mlir][SCF] Fix UB adjustment during scf.for loop peeling Currently when peeling the first iteration, any mentioning of UB within the loop body is replaced with the new UB in the peeled out first iteration. This introduces a bug in the following scenario: Operations inside of the loop that intentionally use the original UB are incorrectly updated. | 9 个月前 | |
[mlir][SCF] Fix UB adjustment during scf.for loop peeling Currently when peeling the first iteration, any mentioning of UB within the loop body is replaced with the new UB in the peeled out first iteration. This introduces a bug in the following scenario: Operations inside of the loop that intentionally use the original UB are incorrectly updated. | 9 个月前 | |
[mlir] Infer SubElementInterface implementations using the storage KeyTy The KeyTy of attribute/type storage classes provide enough information for automatically implementing the necessary sub element interface methods. This removes the need for derived classes to do it themselves, which is both much nicer and easier to handle certain invariants (e.g. null handling). In cases where explicitly handling for parameter types is necessary, they can provide an implementation of AttrTypeSubElementHandler to opt-in to support. This tickles a few things alias wise, which annoyingly messes with tests that hard code specific affine map numbers. Differential Revision: https://reviews.llvm.org/D137374 | 3 年前 | |
[mlir][Pass] Include anchor op in -pass-pipeline In D134622 the printed form of a pass manager is changed to include the name of the op that the pass manager is anchored on. This updates the -pass-pipeline argument format to include the anchor op as well, so that the printed form of a pipeline can be directly passed to -pass-pipeline. In most cases this requires updating -pass-pipeline='pipeline' to -pass-pipeline='builtin.module(pipeline)'. This also fixes an outdated assert that prevented running a PassManager anchored on 'any'. Reviewed By: rriddle Differential Revision: https://reviews.llvm.org/D134900 | 3 年前 | |
[mlir] Extract forall_to_for logic into reusable function and add pass (#89636) This PR extracts the existing scf.forall to scf.for conversion logic inside a transform op (https://github.com/llvm/llvm-project/pull/65474) into a standalone function which can be used in other transformations and adds a scf-forall-to-for pass. | 2 年前 | |
[mlir][scf] Implement conversion from scf.forall to scf.parallel (#94109) There is currently no path to lower scf.forall to scf.parallel with the goal of targeting the OpenMP dialect. In the SCF->ControlFlow conversion, scf.forall is briefly converted to scf.parallel, but the scf.parallel is lowered directly to a sequential loop. This makes experimenting with scf.forall for CPU execution difficult. This change factors out the rewrite in the SCF->ControlFlow pass into a utility function that can then be used in the SCF->ControlFlow lowering and via a separate -scf-forall-to-parallel pass. --------- Co-authored-by: Spenser Bauman <sabauma@fastmail> | 2 年前 | |
[mlir][scf] Rename ForeachThreadOp->ForallOp, PerformConcurrentlyOp->InParallelOp. Differential Revision: https://reviews.llvm.org/D144242 | 3 年前 | |
[MLIR] Revamp RegionBranchOpInterface (#165429) This is still somehow a WIP, we have some issues with this interface that are not trivial to solve. This patch tries to make the concepts of RegionBranchPoint and RegionSuccessor more robust and aligned with their definition: - A RegionBranchPoint is either the parent (RegionBranchOpInterface) op or a RegionBranchTerminatorOpInterface operation in a nested region. - A RegionSuccessor is either one of the nested region or the parent RegionBranchOpInterface Some new methods with reasonnable default implementation are added to help resolving the flow of values across the RegionBranchOpInterface. It is still not trivial in the current state to walk the def-use chain backward with this interface. For example when you have the 3rd block argument in the entry block of a for-loop, finding the matching operands requires to know about the hidden loop iterator block argument and where the iterargs start. The API is designed around forward-tracking of the chain unfortunately. Try to reland #161575 ; I suspect a buildbot incremental build issue. | 9 个月前 | |
[MLIR][SCF] fix loop pipelining pass use of uninitialized value (#146991) fix issue https://github.com/llvm/llvm-project/issues/146990 | 1 年前 | |
| 1 年前 | ||
[mlir][affine]make affine-loop-unroll a FunctionOpInterface pass. (#126475) [mlir][affine]make affine-loop-unroll a FunctionOpInterface pass Make affine-loop-unroll a FunctionOpInterface pass.Now unroll can be done on gpu.func. | 1 年前 | |
[mlir][bufferization] Remove allow-return-allocs and create-deallocs pass options, remove bufferization.escape attribute (#66619) This commit removes the deallocation capabilities of one-shot-bufferization. One-shot-bufferization should never deallocate any memrefs as this should be entirely handled by the ownership-based-buffer-deallocation pass going forward. This means the allow-return-allocs pass option will default to true now, create-deallocs defaults to false and they, as well as the escape attribute indicating whether a memref escapes the current region, will be removed. A new allow-return-allocs-from-loops option is added as a temporary workaround for some bufferization limitations. | 2 年前 | |
[MLIR] Add InParallelOpInterface for parallel combining operations (#157736) This commit: - Introduces a new InParallelOpInterface, along with the ParallelCombiningOpInterface, represent the parallel updating operations we have in a parallel loop of scf.forall. - Change the name of ParallelCombiningOpInterface to InParallelOpInterface as the naming was quite confusing. - ParallelCombiningOpInterface now is used to generalize operations that insert into shared tensors within parallel combining regions. Previously, only tensor.parallel_insert_slice was supported directly in scf.InParallelOp regions. - tensor.parallel_insert_slice now implements ParallelCombiningOpInterface. This change enables future extensions to support additional parallel combining operations beyond tensor.parallel_insert_slice, which have different update semantics, so the in_parallel region can correctly and safely represent these kinds of operation without potential mistakes such as races. Author credits: @qedawkins | 10 个月前 | |
[mlir][bufferization][NFC] Rename to_memref to to_buffer (#137180) As part of the work on transitioning bufferization dialect, ops, and associated logic to operate on newly added type interfaces (see 00eaff3e9c897c263a879416d0f151d7ca7eeaff), rename the bufferization.to_memref to highlight the generic nature of the op. Bufferization process produces buffers while memref is a builtin type rather than a generic term. Preserve the current API (to_buffer still produces a memref), however, as the new type interfaces are not used yet. | 1 年前 | |
[mlir][bufferization] Remove allow-return-allocs and create-deallocs pass options, remove bufferization.escape attribute (#66619) This commit removes the deallocation capabilities of one-shot-bufferization. One-shot-bufferization should never deallocate any memrefs as this should be entirely handled by the ownership-based-buffer-deallocation pass going forward. This means the allow-return-allocs pass option will default to true now, create-deallocs defaults to false and they, as well as the escape attribute indicating whether a memref escapes the current region, will be removed. A new allow-return-allocs-from-loops option is added as a temporary workaround for some bufferization limitations. | 2 年前 | |
[MLIR] Add InParallelOpInterface for parallel combining operations (#157736) This commit: - Introduces a new InParallelOpInterface, along with the ParallelCombiningOpInterface, represent the parallel updating operations we have in a parallel loop of scf.forall. - Change the name of ParallelCombiningOpInterface to InParallelOpInterface as the naming was quite confusing. - ParallelCombiningOpInterface now is used to generalize operations that insert into shared tensors within parallel combining regions. Previously, only tensor.parallel_insert_slice was supported directly in scf.InParallelOp regions. - tensor.parallel_insert_slice now implements ParallelCombiningOpInterface. This change enables future extensions to support additional parallel combining operations beyond tensor.parallel_insert_slice, which have different update semantics, so the in_parallel region can correctly and safely represent these kinds of operation without potential mistakes such as races. Author credits: @qedawkins | 10 个月前 | |
[mlir][bufferize] Make drop-equivalent-buffer-results only support functions that are neither public nor extern (#163001) The callers of public or extern functions are unknown, so their function signatures cannot be changed. | 9 个月前 | |
[mlir][SCF] scf.for: Add support for unsigned integer comparison (#153379) Add a new unit attribute to allow for unsigned integer comparison. Example: mlir scf.for unsigned %iv_32 = %lb_32 to %ub_32 step %step_32 : i32 { // body } Discussion: https://discourse.llvm.org/t/scf-should-scf-for-support-unsigned-comparison/84655 | 11 个月前 | |
[mlir][scf] Add reductions support to scf.parallel fusion (#75955) Properly handle fusion of loops with reductions: * Check there are no first loop results users between loops * Create new loop op with merged reduction init values * Update scf.reduce op to contain reductions from both loops * Update loops users with new loop results | 2 年前 | |
[MLIR][scf.parallel] Don't allow a tile size of 0 (#68762) Fix a crash reported in #64331. The crash is described in the following comment: > It looks like the bug is being caused by the command line argument --scf-parallel-loop-tiling=parallel-loop-tile-sizes=0. More specifically, --scf-parallel-loop-tiling=parallel-loop-tile-sizes sets the tileSize variable to 0 on [this line](https://github.com/llvm/llvm-project/blob/7cc1bfaf371c4a816cf4e62fe31d8515bf8f6fbd/mlir/lib/Dialect/SCF/Transforms/ParallelLoopTiling.cpp#L67). tileSize is then used on [this line](https://github.com/llvm/llvm-project/blob/7cc1bfaf371c4a816cf4e62fe31d8515bf8f6fbd/mlir/lib/Dialect/SCF/Transforms/ParallelLoopTiling.cpp#L117) causing a divide by zero exception. This PR will: 1. Call signalPassFail() when 0 is passed as a tile size. 2. Avoid the divide by zero that causes the crash. Note: This is my first PR for MLIR, so please liberally critique it. | 2 年前 | |
[mlir] Infer SubElementInterface implementations using the storage KeyTy The KeyTy of attribute/type storage classes provide enough information for automatically implementing the necessary sub element interface methods. This removes the need for derived classes to do it themselves, which is both much nicer and easier to handle certain invariants (e.g. null handling). In cases where explicitly handling for parameter types is necessary, they can provide an implementation of AttrTypeSubElementHandler to opt-in to support. This tickles a few things alias wise, which annoyingly messes with tests that hard code specific affine map numbers. Differential Revision: https://reviews.llvm.org/D137374 | 3 年前 | |
[mlir][Pass] Include anchor op in -pass-pipeline In D134622 the printed form of a pass manager is changed to include the name of the op that the pass manager is anchored on. This updates the -pass-pipeline argument format to include the anchor op as well, so that the printed form of a pipeline can be directly passed to -pass-pipeline. In most cases this requires updating -pass-pipeline='pipeline' to -pass-pipeline='builtin.module(pipeline)'. This also fixes an outdated assert that prevented running a PassManager anchored on 'any'. Reviewed By: rriddle Differential Revision: https://reviews.llvm.org/D134900 | 3 年前 | |
[mlir] Infer SubElementInterface implementations using the storage KeyTy The KeyTy of attribute/type storage classes provide enough information for automatically implementing the necessary sub element interface methods. This removes the need for derived classes to do it themselves, which is both much nicer and easier to handle certain invariants (e.g. null handling). In cases where explicitly handling for parameter types is necessary, they can provide an implementation of AttrTypeSubElementHandler to opt-in to support. This tickles a few things alias wise, which annoyingly messes with tests that hard code specific affine map numbers. Differential Revision: https://reviews.llvm.org/D137374 | 3 年前 | |
[mlir][scf] Add parallelLoopUnrollByFactors() (#164958) - In the SCF Utils, add the parallelLoopUnrollByFactors() function to unroll scf::ParallelOp loops according to the specified unroll factors - Add a test pass "TestParallelLoopUnrolling" and the related LIT test - Expose mlir::parallelLoopUnrollByFactors(), mlir::generateUnrolledLoop(), and mlir::scf::computeUbMinusLb() functions in the mlir/Dialect/SCF/Utils/Utils.h and /IR/SCF.h headers to make them available to other passes. - In mlir::generateUnrolledLoop(), add an optional IRMapping *clonedToSrcOpsMap argument to map the new cloned operations to their original ones. In the function body, change the default AnnotateFn type to static const to silence potential warnings about dangling references when a function_ref is assigned to a variable with automatic storage. Signed-off-by: Fabrizio Indirli <Fabrizio.Indirli@arm.com> | 9 个月前 | |
[mlir][scf] Implement Conversion from scf.parallel to Nested scf.for (#147692) Add a utility function/transform operation to convert scf.parallel loops to nested scf.for loops. | 1 年前 | |
Revert "[mlir][loops] Reland Refactor LoopFuseSiblingOp and support parallel fusion #94391 (#97607)" This reverts commit edbc0e30a9e587cee1189be023b9385adc2f239a. Reason for rollback. ASAN complains about this PR: ==4320==ERROR: AddressSanitizer: heap-use-after-free on address 0x502000006cd8 at pc 0x55e2978d63cf bp 0x7ffe6431c2b0 sp 0x7ffe6431c2a8 READ of size 8 at 0x502000006cd8 thread T0 #0 0x55e2978d63ce in map<llvm::MutableArrayRef<mlir::BlockArgument> &, llvm::MutableArrayRef<mlir::BlockArgument>, nullptr> mlir/include/mlir/IR/IRMapping.h:40:11 #1 0x55e2978d63ce in mlir::createFused(mlir::LoopLikeOpInterface, mlir::LoopLikeOpInterface, mlir::RewriterBase&, std::__u::function<llvm::SmallVector<mlir::Value, 6u> (mlir::OpBuilder&, mlir::Location, llvm::ArrayRef<mlir::BlockArgument>)>, llvm::function_ref<void (mlir::RewriterBase&, mlir::LoopLikeOpInterface, mlir::LoopLikeOpInterface&, mlir::IRMapping)>) mlir/lib/Interfaces/LoopLikeInterface.cpp:156:11 #2 0x55e2952a614b in mlir::fuseIndependentSiblingForLoops(mlir::scf::ForOp, mlir::scf::ForOp, mlir::RewriterBase&) mlir/lib/Dialect/SCF/Utils/Utils.cpp:1398:43 #3 0x55e291480c6f in mlir::transform::LoopFuseSiblingOp::apply(mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) mlir/lib/Dialect/SCF/TransformOps/SCFTransformOps.cpp:482:17 #4 0x55e29149ed5e in mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Model<mlir::transform::LoopFuseSiblingOp>::apply(mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Concept const*, mlir::Operation*, mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.h.inc:477:56 #5 0x55e297494a60 in apply blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.cpp.inc:61:14 #6 0x55e297494a60 in mlir::transform::TransformState::applyTransform(mlir::transform::TransformOpInterface) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:953:48 #7 0x55e294646a8d in applySequenceBlock(mlir::Block&, mlir::transform::FailurePropagationMode, mlir::transform::TransformState&, mlir::transform::TransformResults&) mlir/lib/Dialect/Transform/IR/TransformOps.cpp:1788:15 #8 0x55e29464f927 in mlir::transform::NamedSequenceOp::apply(mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) mlir/lib/Dialect/Transform/IR/TransformOps.cpp:2155:10 #9 0x55e2945d28ee in mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Model<mlir::transform::NamedSequenceOp>::apply(mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Concept const*, mlir::Operation*, mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.h.inc:477:56 #10 0x55e297494a60 in apply blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.cpp.inc:61:14 #11 0x55e297494a60 in mlir::transform::TransformState::applyTransform(mlir::transform::TransformOpInterface) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:953:48 #12 0x55e2974a5fe2 in mlir::transform::applyTransforms(mlir::Operation*, mlir::transform::TransformOpInterface, mlir::RaggedArray<llvm::PointerUnion<mlir::Operation*, mlir::Attribute, mlir::Value>> const&, mlir::transform::TransformOptions const&, bool) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:2016:16 #13 0x55e2945888d7 in mlir::transform::applyTransformNamedSequence(mlir::RaggedArray<llvm::PointerUnion<mlir::Operation*, mlir::Attribute, mlir::Value>>, mlir::transform::TransformOpInterface, mlir::ModuleOp, mlir::transform::TransformOptions const&) mlir/lib/Dialect/Transform/Transforms/TransformInterpreterUtils.cpp:234:10 #14 0x55e294582446 in (anonymous namespace)::InterpreterPass::runOnOperation() mlir/lib/Dialect/Transform/Transforms/InterpreterPass.cpp:147:16 #15 0x55e2978e93c6 in operator() mlir/lib/Pass/Pass.cpp:527:17 #16 0x55e2978e93c6 in void llvm::function_ref<void ()>::callback_fn<mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int)::$_1>(long) llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #17 0x55e2978e207a in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #18 0x55e2978e207a in executeAction<mlir::PassExecutionAction, mlir::Pass &> mlir/include/mlir/IR/MLIRContext.h:275:7 #19 0x55e2978e207a in mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) mlir/lib/Pass/Pass.cpp:521:21 #20 0x55e2978e5fbf in runPipeline mlir/lib/Pass/Pass.cpp:593:16 #21 0x55e2978e5fbf in mlir::PassManager::runPasses(mlir::Operation*, mlir::AnalysisManager) mlir/lib/Pass/Pass.cpp:904:10 #22 0x55e2978e5b65 in mlir::PassManager::run(mlir::Operation*) mlir/lib/Pass/Pass.cpp:884:60 #23 0x55e291ebb460 in performActions(llvm::raw_ostream&, std::__u::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:408:17 #24 0x55e291ebabd9 in processBuffer mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:481:9 #25 0x55e291ebabd9 in operator() mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:548:12 #26 0x55e291ebabd9 in llvm::LogicalResult llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>::callback_fn<mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&)::$_0>(long, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&) llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #27 0x55e297b1cffe in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #28 0x55e297b1cffe in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef)::$_0::operator()(llvm::StringRef) const mlir/lib/Support/ToolUtilities.cpp:86:16 #29 0x55e297b1c9c5 in interleave<const llvm::StringRef *, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), (lambda at llvm/include/llvm/ADT/STLExtras.h:2147:49), void> llvm/include/llvm/ADT/STLExtras.h:2125:3 #30 0x55e297b1c9c5 in interleave<llvm::SmallVector<llvm::StringRef, 8U>, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), llvm::raw_ostream, llvm::StringRef> llvm/include/llvm/ADT/STLExtras.h:2147:3 #31 0x55e297b1c9c5 in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef) mlir/lib/Support/ToolUtilities.cpp:89:3 #32 0x55e291eb0cf0 in mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:551:10 #33 0x55e291eb115c in mlir::MlirOptMain(int, char**, llvm::StringRef, llvm::StringRef, mlir::DialectRegistry&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:589:14 #34 0x55e291eb15f8 in mlir::MlirOptMain(int, char**, llvm::StringRef, mlir::DialectRegistry&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:605:10 #35 0x55e29130d1be in main mlir/tools/mlir-opt/mlir-opt.cpp:311:33 #36 0x7fbcf3fff3d3 in __libc_start_main (/usr/grte/v5/lib64/libc.so.6+0x613d3) (BuildId: 9a996398ce14a94560b0c642eb4f6e94) #37 0x55e2912365a9 in _start /usr/grte/v5/debug-src/src/csu/../sysdeps/x86_64/start.S:120 0x502000006cd8 is located 8 bytes inside of 16-byte region [0x502000006cd0,0x502000006ce0) freed by thread T0 here: #0 0x55e29130b7e2 in operator delete(void*, unsigned long) compiler-rt/lib/asan/asan_new_delete.cpp:155:3 #1 0x55e2979eb657 in __libcpp_operator_delete<void *, unsigned long> #2 0x55e2979eb657 in __do_deallocate_handle_size<> #3 0x55e2979eb657 in __libcpp_deallocate #4 0x55e2979eb657 in deallocate #5 0x55e2979eb657 in deallocate #6 0x55e2979eb657 in operator() #7 0x55e2979eb657 in ~vector #8 0x55e2979eb657 in mlir::Block::~Block() mlir/lib/IR/Block.cpp:24:1 #9 0x55e2979ebc17 in deleteNode llvm/include/llvm/ADT/ilist.h:42:39 #10 0x55e2979ebc17 in erase llvm/include/llvm/ADT/ilist.h:205:5 #11 0x55e2979ebc17 in erase llvm/include/llvm/ADT/ilist.h:209:39 #12 0x55e2979ebc17 in mlir::Block::erase() mlir/lib/IR/Block.cpp:67:28 #13 0x55e297aef978 in mlir::RewriterBase::eraseBlock(mlir::Block*) mlir/lib/IR/PatternMatch.cpp:245:10 #14 0x55e297af0563 in mlir::RewriterBase::inlineBlockBefore(mlir::Block*, mlir::Block*, llvm::ilist_iterator<llvm::ilist_detail::node_options<mlir::Operation, false, false, void, false, void>, false, false>, mlir::ValueRange) mlir/lib/IR/PatternMatch.cpp:331:3 #15 0x55e297af06d8 in mlir::RewriterBase::mergeBlocks(mlir::Block*, mlir::Block*, mlir::ValueRange) mlir/lib/IR/PatternMatch.cpp:341:3 #16 0x55e297036608 in mlir::scf::ForOp::replaceWithAdditionalYields(mlir::RewriterBase&, mlir::ValueRange, bool, std::__u::function<llvm::SmallVector<mlir::Value, 6u> (mlir::OpBuilder&, mlir::Location, llvm::ArrayRef<mlir::BlockArgument>)> const&) mlir/lib/Dialect/SCF/IR/SCF.cpp:575:12 #17 0x55e2970673ca in mlir::detail::LoopLikeOpInterfaceInterfaceTraits::Model<mlir::scf::ForOp>::replaceWithAdditionalYields(mlir::detail::LoopLikeOpInterfaceInterfaceTraits::Concept const*, mlir::Operation*, mlir::RewriterBase&, mlir::ValueRange, bool, std::__u::function<llvm::SmallVector<mlir::Value, 6u> (mlir::OpBuilder&, mlir::Location, llvm::ArrayRef<mlir::BlockArgument>)> const&) blaze-out/k8-opt-asan/bin/mlir/include/mlir/Interfaces/LoopLikeInterface.h.inc:658:56 #18 0x55e2978d5feb in replaceWithAdditionalYields blaze-out/k8-opt-asan/bin/mlir/include/mlir/Interfaces/LoopLikeInterface.cpp.inc:105:14 #19 0x55e2978d5feb in mlir::createFused(mlir::LoopLikeOpInterface, mlir::LoopLikeOpInterface, mlir::RewriterBase&, std::__u::function<llvm::SmallVector<mlir::Value, 6u> (mlir::OpBuilder&, mlir::Location, llvm::ArrayRef<mlir::BlockArgument>)>, llvm::function_ref<void (mlir::RewriterBase&, mlir::LoopLikeOpInterface, mlir::LoopLikeOpInterface&, mlir::IRMapping)>) mlir/lib/Interfaces/LoopLikeInterface.cpp:135:14 #20 0x55e2952a614b in mlir::fuseIndependentSiblingForLoops(mlir::scf::ForOp, mlir::scf::ForOp, mlir::RewriterBase&) mlir/lib/Dialect/SCF/Utils/Utils.cpp:1398:43 #21 0x55e291480c6f in mlir::transform::LoopFuseSiblingOp::apply(mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) mlir/lib/Dialect/SCF/TransformOps/SCFTransformOps.cpp:482:17 #22 0x55e29149ed5e in mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Model<mlir::transform::LoopFuseSiblingOp>::apply(mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Concept const*, mlir::Operation*, mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.h.inc:477:56 #23 0x55e297494a60 in apply blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.cpp.inc:61:14 #24 0x55e297494a60 in mlir::transform::TransformState::applyTransform(mlir::transform::TransformOpInterface) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:953:48 #25 0x55e294646a8d in applySequenceBlock(mlir::Block&, mlir::transform::FailurePropagationMode, mlir::transform::TransformState&, mlir::transform::TransformResults&) mlir/lib/Dialect/Transform/IR/TransformOps.cpp:1788:15 #26 0x55e29464f927 in mlir::transform::NamedSequenceOp::apply(mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) mlir/lib/Dialect/Transform/IR/TransformOps.cpp:2155:10 #27 0x55e2945d28ee in mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Model<mlir::transform::NamedSequenceOp>::apply(mlir::transform::detail::TransformOpInterfaceInterfaceTraits::Concept const*, mlir::Operation*, mlir::transform::TransformRewriter&, mlir::transform::TransformResults&, mlir::transform::TransformState&) blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.h.inc:477:56 #28 0x55e297494a60 in apply blaze-out/k8-opt-asan/bin/mlir/include/mlir/Dialect/Transform/Interfaces/TransformInterfaces.cpp.inc:61:14 #29 0x55e297494a60 in mlir::transform::TransformState::applyTransform(mlir::transform::TransformOpInterface) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:953:48 #30 0x55e2974a5fe2 in mlir::transform::applyTransforms(mlir::Operation*, mlir::transform::TransformOpInterface, mlir::RaggedArray<llvm::PointerUnion<mlir::Operation*, mlir::Attribute, mlir::Value>> const&, mlir::transform::TransformOptions const&, bool) mlir/lib/Dialect/Transform/Interfaces/TransformInterfaces.cpp:2016:16 #31 0x55e2945888d7 in mlir::transform::applyTransformNamedSequence(mlir::RaggedArray<llvm::PointerUnion<mlir::Operation*, mlir::Attribute, mlir::Value>>, mlir::transform::TransformOpInterface, mlir::ModuleOp, mlir::transform::TransformOptions const&) mlir/lib/Dialect/Transform/Transforms/TransformInterpreterUtils.cpp:234:10 #32 0x55e294582446 in (anonymous namespace)::InterpreterPass::runOnOperation() mlir/lib/Dialect/Transform/Transforms/InterpreterPass.cpp:147:16 #33 0x55e2978e93c6 in operator() mlir/lib/Pass/Pass.cpp:527:17 #34 0x55e2978e93c6 in void llvm::function_ref<void ()>::callback_fn<mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int)::$_1>(long) llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #35 0x55e2978e207a in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #36 0x55e2978e207a in executeAction<mlir::PassExecutionAction, mlir::Pass &> mlir/include/mlir/IR/MLIRContext.h:275:7 #37 0x55e2978e207a in mlir::detail::OpToOpPassAdaptor::run(mlir::Pass*, mlir::Operation*, mlir::AnalysisManager, bool, unsigned int) mlir/lib/Pass/Pass.cpp:521:21 #38 0x55e2978e5fbf in runPipeline mlir/lib/Pass/Pass.cpp:593:16 #39 0x55e2978e5fbf in mlir::PassManager::runPasses(mlir::Operation*, mlir::AnalysisManager) mlir/lib/Pass/Pass.cpp:904:10 #40 0x55e2978e5b65 in mlir::PassManager::run(mlir::Operation*) mlir/lib/Pass/Pass.cpp:884:60 #41 0x55e291ebb460 in performActions(llvm::raw_ostream&, std::__u::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:408:17 #42 0x55e291ebabd9 in processBuffer mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:481:9 #43 0x55e291ebabd9 in operator() mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:548:12 #44 0x55e291ebabd9 in llvm::LogicalResult llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>::callback_fn<mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&)::$_0>(long, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&) llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #45 0x55e297b1cffe in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #46 0x55e297b1cffe in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef)::$_0::operator()(llvm::StringRef) const mlir/lib/Support/ToolUtilities.cpp:86:16 #47 0x55e297b1c9c5 in interleave<const llvm::StringRef *, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), (lambda at llvm/include/llvm/ADT/STLExtras.h:2147:49), void> llvm/include/llvm/ADT/STLExtras.h:2125:3 #48 0x55e297b1c9c5 in interleave<llvm::SmallVector<llvm::StringRef, 8U>, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), llvm::raw_ostream, llvm::StringRef> llvm/include/llvm/ADT/STLExtras.h:2147:3 #49 0x55e297b1c9c5 in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef) mlir/lib/Support/ToolUtilities.cpp:89:3 #50 0x55e291eb0cf0 in mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:551:10 #51 0x55e291eb115c in mlir::MlirOptMain(int, char**, llvm::StringRef, llvm::StringRef, mlir::DialectRegistry&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:589:14 previously allocated by thread T0 here: #0 0x55e29130ab5d in operator new(unsigned long) compiler-rt/lib/asan/asan_new_delete.cpp:86:3 #1 0x55e2979ed5d4 in __libcpp_operator_new<unsigned long> #2 0x55e2979ed5d4 in __libcpp_allocate #3 0x55e2979ed5d4 in allocate #4 0x55e2979ed5d4 in __allocate_at_least<std::__u::allocator<mlir::BlockArgument> > #5 0x55e2979ed5d4 in __split_buffer #6 0x55e2979ed5d4 in mlir::BlockArgument* std::__u::vector<mlir::BlockArgument, std::__u::allocator<mlir::BlockArgument>>::__push_back_slow_path<mlir::BlockArgument const&>(mlir::BlockArgument const&) #7 0x55e2979ec0f2 in push_back #8 0x55e2979ec0f2 in mlir::Block::addArgument(mlir::Type, mlir::Location) mlir/lib/IR/Block.cpp:154:13 #9 0x55e29796e457 in parseRegionBody mlir/lib/AsmParser/Parser.cpp:2172:34 #10 0x55e29796e457 in (anonymous namespace)::OperationParser::parseRegion(mlir::Region&, llvm::ArrayRef<mlir::OpAsmParser::Argument>, bool) mlir/lib/AsmParser/Parser.cpp:2121:7 #11 0x55e29796b25e in (anonymous namespace)::CustomOpAsmParser::parseRegion(mlir::Region&, llvm::ArrayRef<mlir::OpAsmParser::Argument>, bool) mlir/lib/AsmParser/Parser.cpp:1785:16 #12 0x55e297035742 in mlir::scf::ForOp::parse(mlir::OpAsmParser&, mlir::OperationState&) mlir/lib/Dialect/SCF/IR/SCF.cpp:521:14 #13 0x55e291322c18 in llvm::ParseResult llvm::detail::UniqueFunctionBase<llvm::ParseResult, mlir::OpAsmParser&, mlir::OperationState&>::CallImpl<llvm::ParseResult (*)(mlir::OpAsmParser&, mlir::OperationState&)>(void*, mlir::OpAsmParser&, mlir::OperationState&) llvm/include/llvm/ADT/FunctionExtras.h:220:12 #14 0x55e29795bea3 in operator() llvm/include/llvm/ADT/FunctionExtras.h:384:12 #15 0x55e29795bea3 in callback_fn<llvm::unique_function<llvm::ParseResult (mlir::OpAsmParser &, mlir::OperationState &)> > llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #16 0x55e29795bea3 in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #17 0x55e29795bea3 in parseOperation mlir/lib/AsmParser/Parser.cpp:1521:9 #18 0x55e29795bea3 in parseCustomOperation mlir/lib/AsmParser/Parser.cpp:2017:19 #19 0x55e29795bea3 in (anonymous namespace)::OperationParser::parseOperation() mlir/lib/AsmParser/Parser.cpp:1174:10 #20 0x55e297971d20 in parseBlockBody mlir/lib/AsmParser/Parser.cpp:2296:9 #21 0x55e297971d20 in (anonymous namespace)::OperationParser::parseBlock(mlir::Block*&) mlir/lib/AsmParser/Parser.cpp:2226:12 #22 0x55e29796e4f5 in parseRegionBody mlir/lib/AsmParser/Parser.cpp:2184:7 #23 0x55e29796e4f5 in (anonymous namespace)::OperationParser::parseRegion(mlir::Region&, llvm::ArrayRef<mlir::OpAsmParser::Argument>, bool) mlir/lib/AsmParser/Parser.cpp:2121:7 #24 0x55e29796b25e in (anonymous namespace)::CustomOpAsmParser::parseRegion(mlir::Region&, llvm::ArrayRef<mlir::OpAsmParser::Argument>, bool) mlir/lib/AsmParser/Parser.cpp:1785:16 #25 0x55e29796b2cf in (anonymous namespace)::CustomOpAsmParser::parseOptionalRegion(mlir::Region&, llvm::ArrayRef<mlir::OpAsmParser::Argument>, bool) mlir/lib/AsmParser/Parser.cpp:1796:12 #26 0x55e2978d89ff in mlir::function_interface_impl::parseFunctionOp(mlir::OpAsmParser&, mlir::OperationState&, bool, mlir::StringAttr, llvm::function_ref<mlir::Type (mlir::Builder&, llvm::ArrayRef<mlir::Type>, llvm::ArrayRef<mlir::Type>, mlir::function_interface_impl::VariadicFlag, std::__u::basic_string<char, std::__u::char_traits<char>, std::__u::allocator<char>>&)>, mlir::StringAttr, mlir::StringAttr) mlir/lib/Interfaces/FunctionImplementation.cpp:232:14 #27 0x55e2969ba41d in mlir::func::FuncOp::parse(mlir::OpAsmParser&, mlir::OperationState&) mlir/lib/Dialect/Func/IR/FuncOps.cpp:203:10 #28 0x55e291322c18 in llvm::ParseResult llvm::detail::UniqueFunctionBase<llvm::ParseResult, mlir::OpAsmParser&, mlir::OperationState&>::CallImpl<llvm::ParseResult (*)(mlir::OpAsmParser&, mlir::OperationState&)>(void*, mlir::OpAsmParser&, mlir::OperationState&) llvm/include/llvm/ADT/FunctionExtras.h:220:12 #29 0x55e29795bea3 in operator() llvm/include/llvm/ADT/FunctionExtras.h:384:12 #30 0x55e29795bea3 in callback_fn<llvm::unique_function<llvm::ParseResult (mlir::OpAsmParser &, mlir::OperationState &)> > llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #31 0x55e29795bea3 in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #32 0x55e29795bea3 in parseOperation mlir/lib/AsmParser/Parser.cpp:1521:9 #33 0x55e29795bea3 in parseCustomOperation mlir/lib/AsmParser/Parser.cpp:2017:19 #34 0x55e29795bea3 in (anonymous namespace)::OperationParser::parseOperation() mlir/lib/AsmParser/Parser.cpp:1174:10 #35 0x55e297959b78 in parse mlir/lib/AsmParser/Parser.cpp:2725:20 #36 0x55e297959b78 in mlir::parseAsmSourceFile(llvm::SourceMgr const&, mlir::Block*, mlir::ParserConfig const&, mlir::AsmParserState*, mlir::AsmParserCodeCompleteContext*) mlir/lib/AsmParser/Parser.cpp:2785:41 #37 0x55e29790d5c2 in mlir::parseSourceFile(std::__u::shared_ptr<llvm::SourceMgr> const&, mlir::Block*, mlir::ParserConfig const&, mlir::LocationAttr*) mlir/lib/Parser/Parser.cpp:46:10 #38 0x55e291ebbfe2 in parseSourceFile<mlir::ModuleOp, const std::__u::shared_ptr<llvm::SourceMgr> &> mlir/include/mlir/Parser/Parser.h:159:14 #39 0x55e291ebbfe2 in parseSourceFile<mlir::ModuleOp> mlir/include/mlir/Parser/Parser.h:189:10 #40 0x55e291ebbfe2 in mlir::parseSourceFileForTool(std::__u::shared_ptr<llvm::SourceMgr> const&, mlir::ParserConfig const&, bool) mlir/include/mlir/Tools/ParseUtilities.h:31:12 #41 0x55e291ebb263 in performActions(llvm::raw_ostream&, std::__u::shared_ptr<llvm::SourceMgr> const&, mlir::MLIRContext*, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:383:33 #42 0x55e291ebabd9 in processBuffer mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:481:9 #43 0x55e291ebabd9 in operator() mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:548:12 #44 0x55e291ebabd9 in llvm::LogicalResult llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>::callback_fn<mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&)::$_0>(long, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&) llvm/include/llvm/ADT/STLFunctionalExtras.h:45:12 #45 0x55e297b1cffe in operator() llvm/include/llvm/ADT/STLFunctionalExtras.h:68:12 #46 0x55e297b1cffe in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef)::$_0::operator()(llvm::StringRef) const mlir/lib/Support/ToolUtilities.cpp:86:16 #47 0x55e297b1c9c5 in interleave<const llvm::StringRef *, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), (lambda at llvm/include/llvm/ADT/STLExtras.h:2147:49), void> llvm/include/llvm/ADT/STLExtras.h:2125:3 #48 0x55e297b1c9c5 in interleave<llvm::SmallVector<llvm::StringRef, 8U>, (lambda at mlir/lib/Support/ToolUtilities.cpp:79:23), llvm::raw_ostream, llvm::StringRef> llvm/include/llvm/ADT/STLExtras.h:2147:3 #49 0x55e297b1c9c5 in mlir::splitAndProcessBuffer(std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::function_ref<llvm::LogicalResult (std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, llvm::raw_ostream&)>, llvm::raw_ostream&, llvm::StringRef, llvm::StringRef) mlir/lib/Support/ToolUtilities.cpp:89:3 #50 0x55e291eb0cf0 in mlir::MlirOptMain(llvm::raw_ostream&, std::__u::unique_ptr<llvm::MemoryBuffer, std::__u::default_delete<llvm::MemoryBuffer>>, mlir::DialectRegistry&, mlir::MlirOptMainConfig const&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:551:10 #51 0x55e291eb115c in mlir::MlirOptMain(int, char**, llvm::StringRef, llvm::StringRef, mlir::DialectRegistry&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:589:14 #52 0x55e291eb15f8 in mlir::MlirOptMain(int, char**, llvm::StringRef, mlir::DialectRegistry&) mlir/lib/Tools/mlir-opt/MlirOptMain.cpp:605:10 #53 0x55e29130d1be in main mlir/tools/mlir-opt/mlir-opt.cpp:311:33 #54 0x7fbcf3fff3d3 in __libc_start_main (/usr/grte/v5/lib64/libc.so.6+0x613d3) (BuildId: 9a996398ce14a94560b0c642eb4f6e94) #55 0x55e2912365a9 in _start /usr/grte/v5/debug-src/src/csu/../sysdeps/x86_64/start.S:120 SUMMARY: AddressSanitizer: heap-use-after-free mlir/include/mlir/IR/IRMapping.h:40:11 in map<llvm::MutableArrayRef<mlir::BlockArgument> &, llvm::MutableArrayRef<mlir::BlockArgument>, nullptr> Shadow bytes around the buggy address: 0x502000006a00: fa fa 00 fa fa fa 00 00 fa fa 00 fa fa fa 00 fa 0x502000006a80: fa fa 00 fa fa fa 00 00 fa fa 00 00 fa fa 00 00 0x502000006b00: fa fa 00 00 fa fa 00 00 fa fa 00 fa fa fa 00 fa 0x502000006b80: fa fa 00 fa fa fa 00 fa fa fa 00 00 fa fa 00 00 0x502000006c00: fa fa 00 00 fa fa 00 00 fa fa 00 00 fa fa fd fa =>0x502000006c80: fa fa fd fa fa fa fd fd fa fa fd[fd]fa fa fd fd 0x502000006d00: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa 0x502000006d80: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa 0x502000006e00: fa fa 00 fa fa fa 00 fa fa fa 00 00 fa fa 00 fa 0x502000006e80: fa fa 00 fa fa fa 00 00 fa fa 00 fa fa fa 00 fa 0x502000006f00: fa fa 00 fa fa fa 00 fa fa fa 00 fa fa fa 00 fa Shadow byte legend (one shadow byte represents 8 application bytes): Addressable: 00 Partially addressable: 01 02 03 04 05 06 07 Heap left redzone: fa Freed heap region: fd Stack left redzone: f1 Stack mid redzone: f2 Stack right redzone: f3 Stack after return: f5 Stack use after scope: f8 Global redzone: f9 Global init order: f6 Poisoned by user: f7 Container overflow: fc Array cookie: ac Intra object redzone: bb ASan internal: fe Left alloca redzone: ca Right alloca redzone: cb ==4320==ABORTING | 2 年前 | |
[mlir][SCF] Use Affine ops for indexing math. (#108450) For index type of induction variable, the indexing math is better represented using affine ops such as affine.delinearize_index. This also further demonstrates that some of these affine ops might need to move to a different dialect. For one these ops only support IndexType when they should be able to work with any integer type. This change also includes some canonicalization patterns for affine.delinearize_index operation to 1) Drop unit basis values 2) Remove the delinearize_index op when the linear_index is a loop induction variable of a normalized loop and the basis is of size 1 and is also the upper bound of the normalized loop. --------- Signed-off-by: MaheshRavishankar <mahesh.ravishankar@gmail.com> | 1 年前 | |
[mlir] use transform-interpreter in test passes (#70040) Update most test passes to use the transform-interpreter pass instead of the test-transform-dialect-interpreter-pass. The new "main" interpreter pass has a named entry point instead of looking up the top-level op with PossibleTopLevelOpTrait, which is arguably a more understandable interface. The change is mechanical, rewriting an unnamed sequence into a named one and wrapping the transform IR in to a module when necessary. Add an option to the transform-interpreter pass to target a tagged payload op instead of the root anchor op, which is also useful for repro generation. Only the test in the transform dialect proper and the examples have not been updated yet. These will be updated separately after a more careful consideration of testing coverage of the transform interpreter logic. | 2 年前 | |
[mlir][scf] Implement conversion from scf.forall to scf.parallel (#94109) There is currently no path to lower scf.forall to scf.parallel with the goal of targeting the OpenMP dialect. In the SCF->ControlFlow conversion, scf.forall is briefly converted to scf.parallel, but the scf.parallel is lowered directly to a sequential loop. This makes experimenting with scf.forall for CPU execution difficult. This change factors out the rewrite in the SCF->ControlFlow pass into a utility function that can then be used in the SCF->ControlFlow lowering and via a separate -scf-forall-to-parallel pass. --------- Co-authored-by: Spenser Bauman <sabauma@fastmail> | 2 年前 | |
[mlir][scf] Implement Conversion from scf.parallel to Nested scf.for (#147692) Add a utility function/transform operation to convert scf.parallel loops to nested scf.for loops. | 1 年前 | |
[mlir] use transform-interpreter in test passes (#70040) Update most test passes to use the transform-interpreter pass instead of the test-transform-dialect-interpreter-pass. The new "main" interpreter pass has a named entry point instead of looking up the top-level op with PossibleTopLevelOpTrait, which is arguably a more understandable interface. The change is mechanical, rewriting an unnamed sequence into a named one and wrapping the transform IR in to a module when necessary. Add an option to the transform-interpreter pass to target a tagged payload op instead of the root anchor op, which is also useful for repro generation. Only the test in the transform dialect proper and the examples have not been updated yet. These will be updated separately after a more careful consideration of testing coverage of the transform interpreter logic. | 2 年前 | |
Introduce new Unroll And Jam loop transform for SCF/Affine loops (#94142) Unroll And Jam was supported in affine dialect long time ago using pass. This commit exposes the pattern using transform and in addition adds partial support for SCF loops. | 2 年前 | |
Introduce new Unroll And Jam loop transform for SCF/Affine loops (#94142) Unroll And Jam was supported in affine dialect long time ago using pass. This commit exposes the pattern using transform and in addition adds partial support for SCF loops. | 2 年前 | |
[MLIR] Add a getStaticTripCount method to LoopLikeOpInterface (#158679) This patch adds a getStaticTripCount to the LoopLikeOpInterface, allowing loops to optionally return a static trip count when possible. This is implemented on SCF ForOp, revamping the implementation of constantTripCount, removing redundant duplicate implementations from SCF.cpp. | 10 个月前 | |
[mlir][scf] Allow different forwarding ordering in uplift - Allow 'before' arguments are forwarded in different order to 'after' body when uplifting scf.while to scf.for. | 1 年前 | |
[mlir][scf]: Add value bound for the computed upper bound of for loop (#126426) Add additional bound for the induction variable of the scf.for such that: %iv <= %lower_bound + (%trip_count - 1) * step | 1 年前 | |
[mlir][scf] Fix builder of WhileOp with region builder arguments. The overload of WhileOp::build with arguments for builder functions for the regions of the op was broken: It did not compute correctly the types (and locations) of the region arguments, which lead to failed assertions when the result types were different from the operand types. Specifically, it used the result types (and operand locations) for *both* regions, instead of the operand types (and locations) for the 'before' region and the result types (and loecations) for the 'after' region. Reviewed By: Mogball, mehdi_amini Differential Revision: https://reviews.llvm.org/D142952 | 3 年前 | |
[MLIR][SCF] Define -scf-rotate-while pass (#99850) Define SCF dialect patterns rotating scf.while loops leveraging existing mlir::scf::wrapWhileLoopInZeroTripCheck. forceCreateCheck is always false as the pattern would lead to an infinite recursion otherwise. This pattern rotates scf.while ops, mutating them from "while" loops to "do-while" loops. A guard checking the condition for the first iteration is inserted. Note this guard can be optimized away if the compiler can prove the loop will be executed at least once. Using this pattern, the following while loop: mlir scf.while (%arg0 = %init) : (i32) -> i64 { %val = .., %arg0 : i64 %cond = arith.cmpi .., %arg0 : i32 scf.condition(%cond) %val : i64 } do { ^bb0(%arg1: i64): %next = .., %arg1 : i32 scf.yield %next : i32 } Can be transformed into: mlir %pre_val = .., %init : i64 %pre_cond = arith.cmpi .., %init : i32 scf.if %pre_cond -> i64 { %res = scf.while (%arg1 = %va0) : (i64) -> i64 { // Original after block %next = .., %arg1 : i32 // Original before block %val = .., %next : i64 %cond = arith.cmpi .., %next : i32 scf.condition(%cond) %val : i64 } do { ^bb0(%arg2: i64): %scf.yield %arg2 : i32 } scf.yield %res : i64 } else { scf.yield %pre_val : i64 } The test pass for wrapWhileLoopInZeroTripCheck has been modified to use the new pattern when forceCreateCheck=false. --------- Signed-off-by: Victor Perez <victor.perez@codeplay.com> | 2 年前 |
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