All `apply` functions now have a `TransformRewriter &` parameter. This rewriter should be used to modify the IR. It has a `TrackingListener` attached and updates the internal handle-payload mappings based on rewrites.
Implementations no longer need to create their own `TrackingListener` and `IRRewriter`. Error checking is integrated into `applyTransform`. Tracking listener errors are reported only for ops with the `ReportTrackingListenerFailuresOpTrait` trait attached, allowing for a gradual migration. Furthermore, errors can be silenced with an op attribute.
Additional API will be added to `TransformRewriter` in subsequent revisions. This revision just adds an "empty" `TransformRewriter` class and updates all `apply` implementations.
Differential Revision: https://reviews.llvm.org/D152427
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
Instead of returning an `ArrayRef<Operation *>`, return at iterator that skips ops that were erased/replaced while iterating over the payload ops.
This fixes an issue in conjuction with TrackingListener, where a tracked op was erased during the iteration. Elements may not be removed from an array while iterating over it; this invalidates the iterator.
When ops are erased/removed via `replacePayloadOp`, they are not immediately removed from the mappings data structure. Instead, they are set to `nullptr`. `nullptr`s are not enumerated by `getPayloadOps`. At the end of each transformation, `nullptr`s are removed from the mapping data structure.
Differential Revision: https://reviews.llvm.org/D149847
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
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
Add a verifier checking that if a transform operation consumes a handle
(which is associated with a payload operation being erased or
recreated), it also indicates modification of the payload IR. This
hasn't been consistent in the past because of the "no-aliasing"
assumption where we couldn't have had more than one handle to an
operation, requiring some handle-manipulation operations, such as
`transform.merge_handles` to consume their operands. That assumption has
been liften and it is no longer necessary for these operations to
consume handles and thus make the life harder for the clients.
Additionally, remove TransformEffects.td that uses the ODS mechanism for
indicating side effects that works only for operands and results. It
was being used incorrectly to also indicate effects on the payload IR,
not assocaited with any IR value, and lacked the consume/produce
semantics available via helpers in C++.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D142361
Adapt the implementation of TransformEachOpTrait to the existence of
parameter values recently introduced into the transform dialect. In
particular, allow `applyToOne` hooks to return a list containing a mix
of `Operation *` that will be associated with handles and `Attribute`
that will be associated with parameter values by the trait
implementation of the transform interface's `apply` method.
Disentangle the "transposition" of the list of per-payload op partial
results to decrease its overall complexity and detemplatize the code
that doesn't really need templates. This removes the poorly documented
special handling for single-result ops with TransformEachOpTrait that
could have assigned null pointer values to handles.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D140979
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
In the Transform dialect extensions, provide the separate mechanism to
declare dependent dialects (the dialects the transform IR depends on)
and the generated dialects (the dialects the payload IR may be
transformed into). This allows the Transform dialect clients that are
only constructing the transform IR to avoid loading the dialects
relevant for the payload IR along with the Transform dialect itself,
thus decreasing the build/link time.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D130289
Introduce a transform dialect op that allows one to attempt different
transformation sequences on the same piece of payload IR until one of them
succeeds. This op fundamentally expands the scope of possibilities in the
transform dialect that, until now, could only propagate transformation failure,
at least using in-tree operations. This requires a more detailed specification
of the execution model for the transform dialect that now indicates how failure
is handled and propagated.
Transformations described by transform operations now have tri-state results,
with some errors being fundamentally irrecoverable (e.g., generating malformed
IR) and some others being recoverable by containing ops. Existing transform ops
directly implementing the `apply` interface method are updated to produce this
directly. Transform ops with the `TransformEachTransformOpTrait` are currently
considered to produce only irrecoverable failures and will be updated
separately.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D127724
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
