Update operations in Transform dialect extensions defined in the Affine,
GPU, MemRef and Tensor dialects to use the more generic
`TransformHandleTypeInterface` type constraint instead of hardcoding
`PDL_Operation`. See
https://discourse.llvm.org/t/rfc-type-system-for-the-transform-dialect/65702
for motivation.
Remove the dependency on PDLDialect from these extensions.
Update tests to use `!transform.any_op` instead of `!pdl.operation`.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D150781
Restrict the op to functions and modules. Such ops are modified in-place. The transform now consumes the handle and produces a new handle. The `target_is_module` attribute is no longer needed because a result handle is produced in either case.
Differential Revision: https://reviews.llvm.org/D147446
This allows much better verification messages in consuming ops that properly declare
`TransformHandleTypeInterface` on their operands.
Downstream tests can be updated with a command resembling:
```
git grep -l "structured\.match" mlir/test | xargs -i sed -i {} -e "s/\(structured.match.*\)/\1 : (\!pdl.operation) -> \!pdl.operation/g"
```
Differential Revision: https://reviews.llvm.org/D142643
Introduce a new transform operation to replace `tensor.empty` with
`alloc_tensor` operations. The operation is a pass-through if the target
operation is already a `alloc_tensor`; otherwise, it expects a
`tensor.empty` as a target. Currently, it does not return any results.
The operation is expected to run before `one_shot_bufferize` as
`one_shot_bufferize` rejects `tensor.empty`.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D140026
Expose `function-boundary-type-conversion` in `OneShotBufferizeOp`. To
reuse options between passes and transform operations, create a
`BufferizationEnums.td`.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D137833
Many tests wrap the piece of the IR related to the transform dialect
into `transform.with_pdl_patterns` without actually using PDL patterns
inside. Some of these are leftovers from migration to `structured.match`
and some others are cargo cult, both are useless and pollute the tests.
Reviewed By: guraypp
Differential Revision: https://reviews.llvm.org/D135661
Use the recently introduced TransformTypeInterface instead of hardcoding
the PDLOperationType. This will allow the operations to use more
specific transform types to express pre/post-conditions in the future.
It requires the syntax and Python op construction API to be updated.
Dialect extensions will be switched separately.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D135584
Introduce two different failure propagation mode in the Transform
dialect's Sequence operation. These modes specify whether silenceable
errors produced by nested ops are immediately propagated, thus stopping
the sequence, or suppressed. The latter is useful in end-to-end
transform application scenarios where the user cannot correct the
transformation, but it is robust enough to silenceable failures. It
can be combined with the "alternatives" operation. There is
intentionally no default value to avoid favoring one mode over the
other.
Downstreams can update their tests using:
S='s/sequence \(%.*\) {/sequence \1 failures(propagate) {/'
T='s/sequence {/sequence failures(propagate) {/'
git grep -l transform.sequence | xargs sed -i -e "$S"
git grep -l transform.sequence | xargs sed -i -e "$T"
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D131774
This operation is a NavigationOp that simplifies the writing of transform IR.
Since there is no way of refering to an interface by name, the current implementation uses
an EnumAttr and depends on the interfaces it supports.
In the future, it would be worthwhile to remove this dependence and generalize.
Differential Revision: https://reviews.llvm.org/D130267
This commit allows for One-Shot Bufferize to be used through the transform dialect. No op handle is currently returned for the bufferized IR.
Differential Revision: https://reviews.llvm.org/D125098
