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2025-11-14[MLIR] Extend vector.scatter to accept tensor as base (#165548)Ryutaro Okada
This PR makes the following improvements to `vector.scatter` and its lowering pipeline: - In addition to `memref`, accept a ranked `tensor` as the base operand of `vector.scatter`, similar to `vector.transfer_write`. - Implement bufferization support for `vector.scatter`, so that tensor-based scatter ops can be fully lowered to memref-based forms. It's worth to complete the functionality of map_scatter decomposition. Full discussion can be found here: https://github.com/iree-org/iree/issues/21135 --------- Signed-off-by: Ryutaro Okada <1015ryu88@gmail.com>
2025-08-25[mlir][vector] Rename gather/scatter arguments (nfc) (#153640)Andrzej Warzyński
Renames `indices` as `offsets` and `index_vec` as `indices`. This is primarily to make clearer distinction between the arguments.
2025-07-22[mlir][NFC] update `mlir/Dialect` create APIs (24/n) (#149931)Maksim Levental
See https://github.com/llvm/llvm-project/pull/147168 for more info.
2025-05-28[MLIR] Add bufferization state to `getBufferType` and `resolveConflicts` ↵Michele Scuttari
interface methods (#141466) The PR continues the work started in #141019 by adding the `BufferizationState` class also to the `getBufferType` and `resolveConflicts` interface methods, together with the additional support functions that are used throughout the bufferization infrastructure.
2025-05-23[MLIR] Add bufferization state class to OneShotBufferization pass (#141019)Michele Scuttari
Follow-up on #138143, which was reverted due to a missing update a method signature (more specifically, the bufferization interface for `tensor::ConcatOp`) that was not catched before merging. The old PR description is reported in the next lines. This PR is a follow-up on https://github.com/llvm/llvm-project/pull/138125, and adds a bufferization state class providing information about the IR. The information currently consists of a cached list of symbol tables, which aims to solve the quadratic scaling of the bufferization task with respect to the number of symbols. The PR breaks API compatibility: the bufferize method of the BufferizableOpInterface has been enriched with a reference to a BufferizationState object. The bufferization state must be kept in a valid state by the interface implementations. For example, if an operation with the Symbol trait is inserted or replaced, its parent SymbolTable must be updated accordingly (see, for example, the bufferization of arith::ConstantOp, where the symbol table of the module gets the new global symbol inserted). Similarly, the invalidation of a symbol table must be performed if an operation with the SymbolTable trait is removed (this can be performed using the invalidateSymbolTable method, introduced in https://github.com/llvm/llvm-project/pull/138014).
2025-05-22Revert "[MLIR] Add bufferization state class to OneShotBufferization pass" ↵Michele Scuttari
(#141012) Reverts llvm/llvm-project#138143 The PR for the BufferizationState is temporarily reverted due to API incompatibilities that have been initially missed during the update and were not catched by PR checks.
2025-05-22[MLIR] Add bufferization state class to OneShotBufferization pass (#138143)Michele Scuttari
This PR is a follow-up on #138125, and adds a bufferization state class providing information about the IR. The information currently consists of a cached list of symbol tables, which aims to solve the quadratic scaling of the bufferization task with respect to the number of symbols. The PR breaks API compatibility: the `bufferize` method of the `BufferizableOpInterface` has been enriched with a reference to a `BufferizationState` object. The bufferization state must be kept in a valid state by the interface implementations. For example, if an operation with the `Symbol` trait is inserted or replaced, its parent `SymbolTable` must be updated accordingly (see, for example, the bufferization of `arith::ConstantOp`, where the symbol table of the module gets the new global symbol inserted). Similarly, the invalidation of a symbol table must be performed if an operation with the `SymbolTable` trait is removed (this can be performed using the `invalidateSymbolTable` method, introduced in #138014).
2025-05-12[mlir][vector] Standardize `base` Naming Across Vector Ops (NFC) (#137859)Andrzej Warzyński
[mlir][vector] Standardize base Naming Across Vector Ops (NFC) This change standardizes the naming convention for the argument representing the value to read from or write to in Vector ops that interface with Tensors or MemRefs. Specifically, it ensures that all such ops use the name `base` (i.e., the base address or location to which offsets are applied). Updated operations: * `vector.transfer_read`, * `vector.transfer_write`. For reference, these ops already use `base`: * `vector.load`, `vector.store`, `vector.scatter`, `vector.gather`, `vector.expandload`, `vector.compressstore`, `vector.maskedstore`, `vector.maskedload`. This is a non-functional change (NFC) and does not alter the semantics of these operations. However, it does require users of the XFer ops to switch from `op.getSource()` to `op.getBase()`. To ease the transition, this PR temporarily adds a `getSource()` interface method for compatibility. This is intended for downstream use only and should not be relied on upstream. The method will be removed prior to the LLVM 21 release. Implements #131602
2024-01-17[mlir][IR] Rename "update root" to "modify op" in rewriter API (#78260)Matthias Springer
This commit renames 4 pattern rewriter API functions: * `updateRootInPlace` -> `modifyOpInPlace` * `startRootUpdate` -> `startOpModification` * `finalizeRootUpdate` -> `finalizeOpModification` * `cancelRootUpdate` -> `cancelOpModification` The term "root" is a misnomer. The root is the op that a rewrite pattern matches against (https://mlir.llvm.org/docs/PatternRewriter/#root-operation-name-optional). A rewriter must be notified of all in-place op modifications, not just in-place modifications of the root (https://mlir.llvm.org/docs/PatternRewriter/#pattern-rewriter). The old function names were confusing and have contributed to various broken rewrite patterns. Note: The new function names use the term "modify" instead of "update" for consistency with the `RewriterBase::Listener` terminology (`notifyOperationModified`).
2024-01-12[mlir] Use llvm::is_contained (NFC)Kazu Hirata
2023-08-15[mlir][bufferization] Generalize getAliasingOpResults to getAliasingValuesMatthias Springer
This revision is needed to support bufferization of `cf.br`/`cf.cond_br`. It will also be useful for better analysis of loop ops. This revision generalizes `getAliasingOpResults` to `getAliasingValues`. An OpOperand can now not only alias with OpResults but also with BlockArguments. In the case of `cf.br` (will be added in a later revision): a `cf.br` operand will alias with the corresponding argument of the destination block. If an op does not implement the `BufferizableOpInterface`, the analysis in conservative. It previously assumed that an OpOperand may alias with each OpResult. It now assumes that an OpOperand may alias with each OpResult and each BlockArgument of the entry block. Differential Revision: https://reviews.llvm.org/D157957
2023-06-14[mlir][vector][bufferize] Better analysis for vector.transfer_writeMatthias Springer
The destination operand does not bufferize to a memory read if it is completely overwritten. Differential Revision: https://reviews.llvm.org/D152823
2023-05-12[mlir] Move casting calls from methods to function callsTres Popp
The MLIR classes Type/Attribute/Operation/Op/Value support cast/dyn_cast/isa/dyn_cast_or_null functionality through llvm's doCast functionality in addition to defining methods with the same name. This change begins the migration of uses of the method to the corresponding function call as has been decided as more consistent. Note that there still exist classes that only define methods directly, such as AffineExpr, and this does not include work currently to support a functional cast/isa call. Caveats include: - This clang-tidy script probably has more problems. - This only touches C++ code, so nothing that is being generated. Context: - https://mlir.llvm.org/deprecation/ at "Use the free function variants for dyn_cast/cast/isa/…" - Original discussion at https://discourse.llvm.org/t/preferred-casting-style-going-forward/68443 Implementation: This first patch was created with the following steps. The intention is to only do automated changes at first, so I waste less time if it's reverted, and so the first mass change is more clear as an example to other teams that will need to follow similar steps. Steps are described per line, as comments are removed by git: 0. Retrieve the change from the following to build clang-tidy with an additional check: https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check 1. Build clang-tidy 2. Run clang-tidy over your entire codebase while disabling all checks and enabling the one relevant one. Run on all header files also. 3. Delete .inc files that were also modified, so the next build rebuilds them to a pure state. 4. Some changes have been deleted for the following reasons: - Some files had a variable also named cast - Some files had not included a header file that defines the cast functions - Some files are definitions of the classes that have the casting methods, so the code still refers to the method instead of the function without adding a prefix or removing the method declaration at the same time. ``` ninja -C $BUILD_DIR clang-tidy run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\ -header-filter=mlir/ mlir/* -fix rm -rf $BUILD_DIR/tools/mlir/**/*.inc git restore mlir/lib/IR mlir/lib/Dialect/DLTI/DLTI.cpp\ mlir/lib/Dialect/Complex/IR/ComplexDialect.cpp\ mlir/lib/**/IR/\ mlir/lib/Dialect/SparseTensor/Transforms/SparseVectorization.cpp\ mlir/lib/Dialect/Vector/Transforms/LowerVectorMultiReduction.cpp\ mlir/test/lib/Dialect/Test/TestTypes.cpp\ mlir/test/lib/Dialect/Transform/TestTransformDialectExtension.cpp\ mlir/test/lib/Dialect/Test/TestAttributes.cpp\ mlir/unittests/TableGen/EnumsGenTest.cpp\ mlir/test/python/lib/PythonTestCAPI.cpp\ mlir/include/mlir/IR/ ``` Differential Revision: https://reviews.llvm.org/D150123
2023-02-09[mlir][bufferization] Improve aliasing OpOperand/OpResult propertyMatthias Springer
`getAliasingOpOperands`/`getAliasingOpResults` now encodes OpOperand/OpResult, buffer relation and a degree of certainty. E.g.: ``` // aliasingOpOperands(%r) = {(%t, EQUIV, DEFINITE)} // aliasingOpResults(%t) = {(%r, EQUIV, DEFINITE)} %r = tensor.insert %f into %t[%idx] : tensor<?xf32> // aliasingOpOperands(%r) = {(%t0, EQUIV, MAYBE), (%t1, EQUIV, MAYBE)} // aliasingOpResults(%t0) = {(%r, EQUIV, MAYBE)} // aliasingOpResults(%t1) = {(%r, EQUIV, MAYBE)} %r = arith.select %c, %t0, %t1 : tensor<?xf32> ``` `BufferizableOpInterface::bufferRelation` is removed, as it is now part of `getAliasingOpOperands`/`getAliasingOpResults`. This change allows for better analysis, in particular wrt. equivalence. This allows additional optimizations and better error checking (which is sometimes overly conservative). Examples: * EmptyTensorElimination can eliminate `tensor.empty` inside `scf.if` blocks. This requires a modeling of equivalence: It is not a per-OpResult property anymore. Instead, it can be specified for each OpOperand and OpResult. This is important because `tensor.empty` may be eliminated only if all values on the SSA use-def chain to the final consumer (`tensor.insert_slice`) are equivalent. * The detection of "returning allocs from a block" can be improved. (Addresses a TODO in `assertNoAllocsReturned`.) This allows us to bufferize IR such as "yielding a `tensor.extract_slice` result from an `scf.if` branch", which currently fails to bufferize because the alloc detection is too conservative. * Better bufferization of loops. Aliases of the iter_arg can be yielded (even if they are not equivalent) without having to realloc and copy the entire buffer on each iteration. The above-mentioned examples are not yet implemented with this change. This change just improves the BufferizableOpInterface, its implementations and related helper functions, so that better aliasing information is available for each op. Differential Revision: https://reviews.llvm.org/D142129
2023-02-01[mlir][bufferization][NFC] Rename getAliasingOpOperand/getAliasingOpResultMatthias Springer
* `getAliasingOpOperand` => `getAliasingOpOperands` * `getAliasingOpResult` => `getAliasingOpResults` Also a few minor code cleanups and better documentation. Differential Revision: https://reviews.llvm.org/D142979
2023-01-31[mlir][vector][bufferize] Fix Windows build failure introduced by D141686Matthias Springer
2023-01-31[mlir][vector][bufferize] Bufferize vector.mask and vector.yieldMatthias Springer
The masked op can currently not bufferize out-of-place. Such IR would be rejected by the One-Shot Bufferize because it would mean that a new buffer allocation is yielded from a block. Furthermore, only one operation is currently allowed inside `vector.mask`. Differential Revision: https://reviews.llvm.org/D141686
2022-10-27[mlir][vector][bufferize] Implement DestinationStyleOpInterface on ↵Matthias Springer
TransferWriteOp This simplifies the BufferizableOpInterface implementation of vector.transfer_write. Differential Revision: https://reviews.llvm.org/D136348
2022-08-09[MLIR] Extend vector.gather to accept tensor as baseJerry Wu
In addition to memref, accept ranked tensor as the base operand of vector.gather, similar to vector.trasnfer_read. This will allow us to vectorize noncontiguous tensor.extract into vector.gather. Full discussion can be found here: https://github.com/iree-org/iree/issues/9198 Reviewed By: hanchung, dcaballe Differential Revision: https://reviews.llvm.org/D130097
2022-07-07[mlir][vector][bufferize] Fix transfer_write dropping mask operandMatthias Springer
Differential Revision: https://reviews.llvm.org/D129253
2022-06-27[mlir][bufferization][NFC] Add error handling to getBufferMatthias Springer
This is in preparation of adding memory space support. Differential Revision: https://reviews.llvm.org/D128277
2022-06-17[mlir][bufferize][NFC] Remove BufferizationStateMatthias Springer
With the recent refactorings, this class is no longer needed. We can use BufferizationOptions in all places were BufferizationState was used. Differential Revision: https://reviews.llvm.org/D127653
2022-06-17[mlir][bufferize] Bufferize after TensorCopyInsertionMatthias Springer
This change changes the bufferization so that it utilizes the new TensorCopyInsertion pass. One-Shot Bufferize no longer calls the One-Shot Analysis. Instead, it relies on the TensorCopyInsertion pass to make the entire IR fully inplacable. The `bufferize` implementations of all ops are simplified; they no longer have to account for out-of-place bufferization decisions. These were already materialized in the IR in the form of `bufferization.alloc_tensor` ops during the TensorCopyInsertion pass. Differential Revision: https://reviews.llvm.org/D127652
2022-03-28[mlir] Flip Vector dialect accessors used to prefixed form.Jacques Pienaar
This has been on _Both for a couple of weeks. Flip usages in core with intention to flip flag to _Prefixed in follow up. Needed to add a couple of helper methods in AffineOps and Linalg to facilitate a pure flag flip in follow up as some of these classes are used in templates and so sensitive to Vector dialect changes. Differential Revision: https://reviews.llvm.org/D122151
2022-03-16[mlir] Refactor DialectRegistry delayed interface support into a general ↵River Riddle
DialectExtension mechanism The current dialect registry allows for attaching delayed interfaces, that are added to attrs/dialects/ops/etc. when the owning dialect gets loaded. This is clunky for quite a few reasons, e.g. each interface type has a separate tracking structure, and is also quite limiting. This commit refactors this delayed mutation of dialect constructs into a more general DialectExtension mechanism. This mechanism is essentially a registration callback that is invoked when a set of dialects have been loaded. This allows for attaching interfaces directly on the loaded constructs, and also allows for loading new dependent dialects. The latter of which is extremely useful as it will now enable dependent dialects to only apply in the contexts in which they are necessary. For example, a dialect dependency can now be conditional on if a user actually needs the interface that relies on it. Differential Revision: https://reviews.llvm.org/D120367
2022-03-15[mlir][bufferize][NFC] Split BufferizationState into ↵Matthias Springer
AnalysisState/BufferizationState Differential Revision: https://reviews.llvm.org/D121361
2022-02-09[mlir][bufferize] OpOperands can have multiple aliasing OpResultsMatthias Springer
This makes getAliasingOpResult symmetric to getAliasingOpOperand. The previous implementation was confusing for users and implemented in such a way only because there are currently no bufferizable ops that have multiple aliasing OpResults. Differential Revision: https://reviews.llvm.org/D119259
2022-02-01[mlir][bufferize][NFC] Move vector BufferizableOpInterface impl to vector ↵Matthias Springer
dialect Differential Revision: https://reviews.llvm.org/D118540