[all-commits] [llvm/llvm-project] 8f2d83: [mlir][bufferization] Add `BufferizableOpInterface...

[Matthias Springer via All-commits]

  Branch: refs/heads/main
  Home:   https://github.com/llvm/llvm-project
  Commit: 8f2d83da260fc7e1334ee975d9b00344aab51410
      https://github.com/llvm/llvm-project/commit/8f2d83da260fc7e1334ee975d9b00344aab51410
  Author: Matthias Springer <me at m-sp.org>
  Date:   2024-01-16 (Tue, 16 Jan 2024)

  Changed paths:
    M mlir/include/mlir/Dialect/Bufferization/IR/BufferizableOpInterface.h
    M mlir/include/mlir/Dialect/Bufferization/IR/BufferizableOpInterface.td
    M mlir/lib/Dialect/Bufferization/IR/BufferizableOpInterface.cpp
    M mlir/lib/Dialect/Bufferization/Transforms/Bufferize.cpp
    M mlir/lib/Dialect/Bufferization/Transforms/FuncBufferizableOpInterfaceImpl.cpp
    M mlir/lib/Dialect/Bufferization/Transforms/OneShotAnalysis.cpp
    M mlir/lib/Dialect/Bufferization/Transforms/OneShotModuleBufferize.cpp

  Log Message:
  -----------
  [mlir][bufferization] Add `BufferizableOpInterface::hasTensorSemantics` (#75273)

Add a new interface method to `BufferizableOpInterface`:
`hasTensorSemantics`. This method returns "true" if the op has tensor
semantics and should be bufferized.

Until now, we assumed that an op has tensor semantics if it has tensor
operands and/or tensor op results. However, there are ops like
`ml_program.global` that do not have any results/operands but must still
be bufferized (#75103). The new interface method can return "true" for
such ops.

This change also decouples `bufferization::bufferizeOp` a bit from the
func dialect.