Since #130487, `tensor.extract_slice` and `tensor.insert_slice` ops that
are statically detected to go out of bounds are rejected by the
verifier.
This commit fixes canonicalization patterns that currently fold
dynamically out-of-bounds ops (valid IR) to statically out-of-bounds ops
(invalid IR).
This patch adds a default memory space attribute to the DL and adds
methods to query the attribute. This is required as MLIR has no well
defined default memory space unlike LLVM which has 0. While `nullptr` is
a candidate for default memory space, the `ptr` dialect will remove the
possibility for `nullptr` memory spaces to avoid undefined semantics.
This patch also modifies the `DataLayoutTypeInterface::areCompatible` to
include the new DL spec and merged entries, as it is needed to query the default memory
space.
---------
Co-authored-by: Christian Ulmann <christianulmann@gmail.com>
This PR makes sure that we always use `Type::isIntOrFloat` rather than
re-implementing this condition inline. Also, it removes `isScalarType`
that effectively re-implemented this method.
Add mangling style as a spec entry to datalayout, and implemented
importing and exporting LLVM IR to MLIR (LLVM dialect).
Its represented as string as the scope of this PR is to preserve info
from LLVM IR, so client in MLIR still need to map deduce the meaning of
the string, like "e" means ELF, "o" for Mach-O, etc.
it addresses one of issues mentioned in this
[issue](https://github.com/llvm/llvm-project/issues/126046)
Enable ops with only read side effects in scf.for to be hoisted with a
scf.if guard that checks against the trip count
This patch takes a step towards a less conservative LICM in MLIR as
discussed in the following discourse thread:
[Speculative LICM?](https://discourse.llvm.org/t/speculative-licm/80977)
This patch in particular does the following:
1. Relaxes the original constraint for hoisting that only hoists ops
without any side effects. This patch also allows the ops with only read
side effects to be hoisted into an scf.if guard only if every op in the
loop or its nested regions is side-effect free or has only read side
effects. This scf.if guard wraps the original scf.for and checks for
**trip_count > 0**.
2. To support this, two new interface methods are added to
**LoopLikeInterface**: _wrapInTripCountCheck_ and
_unwrapTripCountCheck_. Implementation starts with wrapping the scf.for
loop into scf.if guard using _wrapInTripCountCheck_ and if there is no
op hoisted into the this guard after we are done processing the
worklist, it unwraps the guard by calling _unwrapTripCountCheck_.
This patch shares core interface methods dealing with argument and
result attributes from CallableOpInterface with the CallOpInterface and
makes them mandatory to gives more consistent guarantees about concrete
operations using these interfaces.
This allows adding argument attributes on call like operations, which is
sometimes required to get proper ABI, like with llvm.call (and llvm.invoke).
The patch adds optional `arg_attrs` and `res_attrs` attributes to operations using
these interfaces that did not have that already.
They can then re-use the common "rich function signature"
printing/parsing helpers if they want (for the LLVM dialect, this is
done in the next patch).
Part of RFC: https://discourse.llvm.org/t/mlir-rfc-adding-argument-and-result-attributes-to-llvm-call/84107
Implement the integer range inference niterface for memref.dim and
tetnor.dim using shared code. The inference will infer the `dim` of
dynamic dimensions to [0, index_max] and take the union of all the
dimensions that the `dim` argument could be validly referring to.
The op carries the output-shape directly. This can be used directly.
Also adds a method to get the shape as a `SmallVector<OpFoldResult>`.
Signed-off-by: MaheshRavishankar <mahesh.ravishankar@gmail.com>
Ranges let us push the whole blocks onto the queue in constant time. If
one of the first ops in the block is side-effecting we'll be able to
provide the answer quickly. The previous implementation had to walk the
block and queue all the operations only to start traversing them again,
which was a considerable slowdown for compile times of large MLIR
programs in our benchmarks.
---------
Co-authored-by: Jacques Pienaar <jpienaar@google.com>
There is a special case in `arith.ceildivsi` range inference for
handling `lhs.smin()==INT_MIN`, but when `lhs` is not a single value, it
can cause it to skip entire negative range. Add `lhs.smin() + 1` check
to handle it.
Note that PointerUnion::{is,get} have been soft deprecated in
PointerUnion.h:
// FIXME: Replace the uses of is(), get() and dyn_cast() with
// isa<T>, cast<T> and the llvm::dyn_cast<T>
I'm not touching PointerUnion::dyn_cast for now because it's a bit
complicated; we could blindly migrate it to dyn_cast_if_present, but
we should probably use dyn_cast when the operand is known to be
non-null.
Previous impl was getting incorrect results for widths > i1 and was
disabled.
While same algorithm can be used for `andi` and `ori` too, without
additional modifications it will produce less precise result.
Fixes https://github.com/llvm/llvm-project/issues/82168
`intrange::inferXor` was incorrectly handling ranges for widths > i1
(see example in code). Limit it to i1 for now. For bigger widths it will
return maxRange.
Fixes#115293
While the definition of ceildivsi is integer division, rounding up, most
implementations will use `-(-a / b)` for dividing `a ceildiv b` with `a`
negative and `b` positive.
Mathematically, and for most integers, these two definitions are
equivalent. However, with `a == INT_MIN`, the initial negation is a
noop, which means that, while divinding and rounding up would give a
negative result, `-((- INT_MIN) / b)` is `-(INT_MIN / b)`, which is
positive.
This commit adds a special case to ceilDivSI inference to handle this
case and bring it in line with the operational instead of the
mathematical semantics of ceiling division.
PR #112292 added support for vectors to the integer range inference
interface and analysis, but didn't update the getDestWidth() method.
This caused crashes when trying to infer the ranges of `arith.extsi`
with vector inputs, as the code would try to sign-extend a N-bit value
to a 0-bit one, which would assert and crash.
This commit fixes the issue by adding a getElementTypeOrSelf().
Unifies parsing and printing for DLTI attributes. Introduces a format of
`#dlti.attr<key1 = val1, ..., keyN = valN>` syntax for all queryable
DLTI attributes similar to that of the DictionaryAttr, while retaining
support for specifying key-value pairs with `#dlti.dl_entry` (whether to
retain this is TBD).
As the new format does away with most of the boilerplate, it is much easier
to parse for humans. This makes an especially big difference for nested
attributes.
Updates the DLTI-using tests and includes fixes for misc error checking/
error messages.
Print an error such as the following one before terminating program
execution.
```
mlir/test/Dialect/SparseTensor/convert_dense2sparse.mlir:26:8: remark: location of op
%0 = sparse_tensor.convert %arg0 : tensor<?xi32> to tensor<?xi32, #SparseVector>
^
LLVM ERROR: Failed to infer result type(s):
"sparse_tensor.positions"(...) {} : (index) -> ( ??? )
(stack trace follows)
```
- **[MLIR] Add test for inferring range of remu; NFC**
- **[MLIR] Unconditionally take min of max lhs/rhs value in inferRemU**
`arith.remu` cannot be larger than (rhs - 1) or lhs.
As specified in the docs,
1) raw_string_ostream is always unbuffered and
2) the underlying buffer may be used directly
( 65b13610a5226b84889b923bae884ba395ad084d for further reference )
* Don't call raw_string_ostream::flush(), which is essentially a no-op.
* Avoid unneeded calls to raw_string_ostream::str(), to avoid excess indirection.
Allow customization of the `resolveCallable` method in the
`CallOpInterface`. This change allows for operations implementing this
interface to provide their own logic for resolving callables.
- Introduce the `resolveCallable` method, which does not include the
optional symbol table parameter. This method replaces the previously
existing extra class declaration `resolveCallable`.
- Introduce the `resolveCallableInTable` method, which incorporates the
symbol table parameter. This method replaces the previous extra class
declaration `resolveCallable` that used the optional symbol table
parameter.
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
The refactor had a bug where the fused loop was inserted in an incorrect
location. This patch fixes the bug and relands the original PR
https://github.com/llvm/llvm-project/pull/94391.
This patch refactors code related to LoopFuseSiblingOp transform in
attempt to reduce duplicate common code. The aim is to refactor as much
as possible to a functions on LoopLikeOpInterfaces, but this is still a
work in progress. A full refactor will require more additions to the
LoopLikeOpInterface.
In addition, scf.parallel fusion support has been added.
This patch refactors code related to `LoopFuseSiblingOp` transform in
attempt to reduce duplicate common code. The aim is to refactor as much
as possible to a functions on `LoopLikeOpInterface`s, but this is still
a work in progress. A full refactor will require more additions to the
`LoopLikeOpInterface`.
In addition, `scf.parallel` fusion support has been added.
**Rationale**
- With the current flexibility of supporting any type of value, we will
need to offer type-specific APIs to fetch a value (e.g.,
`getDevicePropertyValueAsInt` for integer type,
`getDevicePropertyValueAsFloat` for float type, etc.) A single type of
value will eliminate this need.
- Current flexibility can also lead to typing errors when a user fetches
the value of a property using an API that is not consistent with the
type of the value.
**What is the change**
For following system description,
```
module attributes {
dlti.target_system_spec = #dlti.target_system_spec<
"CPU": #dlti.target_device_spec<
#dlti.dl_entry<"max_vector_op_width", 64.0 : f32>>,
"GPU": #dlti.target_device_spec<
#dlti.dl_entry<"max_vector_op_width", 128 : ui32>>
>} {}
```
a user no longer needs to use `getDevicePropertyValueAsInt` for
retrieving GPU's `max_vector_op_width` and
`getDevicePropertyValueAsFloat` for retrieving CPU's
`max_vector_op_width`. Instead it can be done with a uniform API of
`getDevicePropertyValue`.
As of today, Android's libcxx is missing C++17's std::function's CTAD
added in e1eabcdfad89f67ae575b0c86aa4a72d277378b4. This leads to
InferIntRangeCommon.cpp to fail to compile. This commit makes the
template parameter of std::function in that function explicit, therefore
avoiding CTAD. While LLVM/MLIR's requirement is C++17, the rest of the
code builds fine so hopefully this is acceptable.
and Interfaces. This is a newer implementation of PR
https://github.com/llvm/llvm-project/pull/85141 and
[RFC](https://discourse.llvm.org/t/rfc-target-description-and-cost-model-in-mlir/76990)
by considering reviews and comments on the original PR.
As an example of attributes supported by this commit:
```
module attributes {
dlti.target_system_spec =
#dlti.target_device_spec<
#dlti.dl_entry<"dlti.device_id", 0: ui32>,
#dlti.dl_entry<"dlti.device_type", "CPU">,
#dlti.dl_entry<"dlti.L1_cache_size_in_bytes", 8192 : ui32>>,
#dlti.target_device_spec <
#dlti.dl_entry<"dlti.device_id", 1: ui32>,
#dlti.dl_entry<"dlti.device_type", "GPU">,
#dlti.dl_entry<"dlti.max_vector_op_width", 64 : ui32>>,
#dlti.target_device_spec <
#dlti.dl_entry<"dlti.device_id", 2: ui32>,
#dlti.dl_entry<"dlti.device_type", "XPU">>>
}
```
This patch adds more precise side effects to the current ops with memory
effects, allowing us to determine which OpOperand/OpResult/BlockArgument
the
operation reads or writes, rather than just recording the reading and
writing
of values. This allows for convenient use of precise side effects to
achieve
analysis and optimization.
Related discussions:
https://discourse.llvm.org/t/rfc-add-operandindex-to-sideeffect-instance/79243
This patch adds support for computing bounds for semi-affine mod
expression to FlatLinearConstraints. This is then enabled within the
ScalableValueBoundsConstraintSet to allow computing the bounds of
scalable remainder loops.
E.g. computing the bound of something like:
```
// `1000 mod s0` is a semi-affine.
#remainder_start_index = affine_map<()[s0] -> (-(1000 mod s0) + 1000)>
#remaining_iterations = affine_map<(d0) -> (-d0 + 1000)>
%0 = affine.apply #remainder_start_index()[%c8_vscale]
scf.for %i = %0 to %c1000 step %c8_vscale {
%remaining_iterations = affine.apply #remaining_iterations(%i)
// The upper bound for the remainder loop iterations should be:
// %c8_vscale - 1 (expressed as an affine map,
// affine_map<()[s0] -> (s0 * 8 - 1)>, where s0 is vscale)
%bound = "test.reify_bound"(%remaining_iterations) <{scalable, ...}>
}
```
There are caveats to this implementation. To be able to add a bound for
a `mod` we need to assume the rhs is positive (> 0). This may not be
known when adding the bounds for the `mod` expression. So to handle this
a constraint is added for `rhs > 0`, this may later be found not to hold
(in which case the constraints set becomes empty/invalid).
This is not a problem for computing scalable bounds where it's safe to
assume `s0` is vscale (or some positive multiple of it). But this may
need to be considered when enabling this feature elsewhere (to ensure
correctness).
Integer range analysis will not update the range of an operation when
any of the inferred input lattices are uninitialized. In the current
behavior, all lattice values for non integer types are uninitialized.
For operations like arith.cmpf
```mlir
%3 = arith.cmpf ugt, %arg0, %arg1 : f32
```
that will result in the range of the output also being uninitialized,
and so on for any consumer of the arith.cmpf result. When control-flow
ops are involved, the lack of propagation results in incorrect ranges,
as the back edges for loop carried values are not properly joined with
the definitions from the body region.
For example, an scf.while loop whose body region produces a value that
is in a dataflow relationship with some floating-point values through an
arith.cmpf operation:
```mlir
func.func @test_bad_range(%arg0: f32, %arg1: f32) -> (index, index) {
%c4 = arith.constant 4 : index
%c1 = arith.constant 1 : index
%c0 = arith.constant 0 : index
%3 = arith.cmpf ugt, %arg0, %arg1 : f32
%1:2 = scf.while (%arg2 = %c0, %arg3 = %c0) : (index, index) -> (index, index) {
%2 = arith.cmpi ult, %arg2, %c4 : index
scf.condition(%2) %arg2, %arg3 : index, index
} do {
^bb0(%arg2: index, %arg3: index):
%4 = arith.select %3, %arg3, %arg3 : index
%5 = arith.addi %arg2, %c1 : index
scf.yield %5, %4 : index, index
}
return %1#0, %1#1 : index, index
}
```
The existing behavior results in the control condition %2 being
optimized to true, turning the while loop into an infinite loop. The
update to %arg2 through the body region is never factored into the range
calculation, as the ranges for the body ops all test as uninitialized.
This change causes all values initialized with setToEntryState to be set
to some initialized range, even if the values are not integers.
---------
Co-authored-by: Spenser Bauman <sabauma@fastmail>
This patch includes the "no signed wrap" and "no unsigned wrap" flags,
which can be used to annotate some Ops in the `arith` dialect and also
in LLVMIR, in the integer range inference.
The general approach is to use saturating arithmetic operations to infer
bounds which are assumed to not wrap and use overflowing arithmetic
operations in the normal case. If overflow is detected in the normal
case,
special handling makes sure that we don't underestimate the result
range.
When an overflow happens during shift left, i.e. the last sign bit or
the most significant data bit gets shifted out, the current approach of
inferring the range of results does not work anymore.
This patch checks for possible overflow and returns the max range in
that case.
Fix https://github.com/llvm/llvm-project/issues/82158
This patch is a first pass at making consistent syntax across the
`LinalgTransformOp`s that use dynamic index lists for size parameters.
Previously, there were two different forms: inline types in the list, or
place them in the functional style tuple. This patch goes for the
latter.
In order to do this, the `printPackedOrDynamicIndexList`,
`printDynamicIndexList` and their `parse` counterparts were modified so
that the types can be optionally provided to the corresponding custom
directives.
All affected ops now use tablegen `assemblyFormat`, so custom
`parse`/`print` functions have been removed. There are a couple ops that
will likely add dynamic size support, and once that happens it should be
made sure that the assembly remains consistent with the changes in this
patch.
The affected ops are as follows: `pack`, `pack_greedily`,
`tile_using_forall`. The `tile_using_for` and `vectorize` ops already
used this syntax, but their custom assembly was removed.
---------
Co-authored-by: Oleksandr "Alex" Zinenko <ftynse@gmail.com>
This commit implements runtime verification for LinalgStructuredOps
using the existing `RuntimeVerifiableOpInterface`. The verification
checks that the runtime sizes of the operands match the runtime sizes
inferred by composing the loop ranges with the op's indexing maps.
This commit implements runtime verification for LinalgStructuredOps
using the existing `RuntimeVerifiableOpInterface`. The verification
checks that the runtime sizes of the operands match the runtime sizes
inferred by composing the loop ranges with the op's indexing maps.
This commit extends the data layout to support scalable vectors. For
scalable vectors, the `TypeSize`'s scalable field is set accordingly,
and the alignment information remains the same as for normal vectors.
This behavior is in sync with what LLVM's data layout queries are
producing.
Before this change, scalable vectors incorrectly returned the same size
as "normal" vectors.
