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path: root/mlir/lib/Dialect/Tensor/Transforms/IndependenceTransforms.cpp
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2025-07-25[mlir][NFC] update `mlir/Dialect` create APIs (33/n) (#150659)Maksim Levental
See https://github.com/llvm/llvm-project/pull/147168 for more info.
2025-07-23[mlir][NFC] update `mlir/Dialect` create APIs (23/n) (#149930)Maksim Levental
See https://github.com/llvm/llvm-project/pull/147168 for more info.
2025-07-11[mlir] Remove unused includes (NFC) (#148119)Kazu Hirata
These are identified by misc-include-cleaner. I've filtered out those that break builds. Also, I'm staying away from llvm-config.h, config.h, and Compiler.h, which likely cause platform- or compiler-specific build failures.
2024-12-20[Tensor] Migrate away from PointerUnion::{is,get} (NFC) (#120679)Kazu Hirata
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.
2024-04-16[mlir][Interfaces] `Variable` abstraction for `ValueBoundsOpInterface` (#87980)Matthias Springer
This commit generalizes and cleans up the `ValueBoundsConstraintSet` API. The API used to provide function overloads for comparing/computing bounds of: - index-typed SSA value - dimension of shaped value - affine map + operands This commit removes all overloads. There is now a single entry point for each `compare` variant and each `computeBound` variant. These functions now take a `Variable`, which is internally represented as an affine map and map operands. This commit also adds support for computing bounds for an affine map + operands. There was previously no public API for that.
2023-04-28[mlir][tensor] Add transform to make tensor.pad loop-independentMatthias Springer
Add a transform to make `tensor.pad` and `tensor.empty` ops independent of SCF loop IVs. Such ops can then be hoisted. E.g.: ``` scf.for %iv = %lb to %ub step %step { %high = affine.apply affine_map<(d0)[s0] -> (s0 - d0)> (%i)[%ub] %p = tensor.pad %t low[5] high[%high] ... ... } ``` Is transformed to: ``` %high_new = affine.apply affine_map<()[s0, s1] -> (-s0 + s1)> ()[%lb, %ub] %p_hoistable = tensor.pad %t low[5] high[%high_new] %dim = tensor.dim %t, %c0 %size = affine.apply affine_map<(d0)[s0, s1] -> (-d0 + s0 + s1 + 5)>(%iv)[%ub, %dim] %slice = tensor.extract_slice %p_hoistable [0] [%size] [1] ``` Differential Revision: https://reviews.llvm.org/D143910