There is a use case that we need to peel the first iteration out of the
for loop so that the peeled forOp can be canonicalized away and the
fillOp can be fused into the inner forall loop. For example, we have
nested loops as below
```
linalg.fill ins(...) outs(...)
scf.for %arg = %lb to %ub step %step
scf.forall ...
```
After the peeling transform, it is expected to be
```
scf.forall ...
linalg.fill ins(...) outs(...)
scf.for %arg = %(lb + step) to %ub step %step
scf.forall ...
```
This patch makes the most use of the existing peeling functions and adds
support for peeling the first iteration out of the loop.
This patch updates `transform.loop.peel` so that this Op returns two
rather than one handle:
* one for the peeled loop, and
* one for the remainder loop.
Also, following this change this Op will fail if peeling fails. This is
consistent with other similar Ops that also fail if no transformation
takes place.
Relands #67482 with an extra fix for transform_loop_ext.py
This patch updates `transform.loop.peel` so that this Op returns two
rather than one handle:
* one for the peeled loop, and
* one for the remainder loop.
Also, following this change this Op will fail if peeling fails. This is
consistent with other similar Ops that also fail if no transformation
takes place.
Add a straightforward sequentialization transform from `scf.forall` to a
nest of `scf.for` in absence of results and expose it as a transform op.
This is helpful in combination with other transform ops, particularly
fusion, that work best on parallel-by-construction `scf.forall` but
later need to target sequential `for` loops.
This change adds a method to modify the ConversionTarget used during
`transform.apply_conversion_patterns` to the
`ConversionPatternDescriptorOpInterface`. This is needed when the TypeConverter
is used to dictate the dynamic legality of operations, as in "structural"
conversion patterns present in, for example, the SCF and func dialects.
As a first use case/test, this change also adds a
`transform.apply_patterns.scf.structural_conversions` operation to the SCF
dialect.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D158672
This patch adds a new transform operation `transform.loop.fuse_sibling`,
which given two loops, fuses them, assuming that they are independent.
The transform operation itself performs very basic checks to ensure
IR legality, and leaves the responsibility of ensuring independence on the user.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D157069
This transform op promotes loops with one iteration. I.e., the loop op is replaced by just the loop body.
Differential Revision: https://reviews.llvm.org/D154361
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
* Remove `transform::PatternRegistry`.
* Add a new op for each currently registered pattern set.
* Change names of vector dialect pattern selector ops, so that they are consistent with the remaining code base.
* Remove redundant `transform.vector.extract_address_computations` op.
Differential Revision: https://reviews.llvm.org/D152249
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
Outlining is particularly interesting when the outlined function is
replaced with something else, e.g., a microkernel. It is good to have a
handle to the call in this case.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D149849
Given an scf.if conditional, using this transformation is akin to injecting
user-specified information that it is always safe to execute only the specified
`if` or `else` branch.
This is achieved by just replacing the scf.if by the content of one of its
branches.
This is particularly useful for user-controlled rewriting of conditionals
that exist solely to guard against out-of-bounds behavior.
At the moment, no assume or assert operation is emitted as it is not always
desirable. In the future, this may be controlled by a dedicated attribute.
Differential Revision: https://reviews.llvm.org/D148125
Simplify the handling of silenceable failures in the transform dialect.
Previously, the logic of `TransformEachOpTrait` required that
`applyToEach` returned a list of null pointers when a silenceable
failure was emitted. This was not done consistently and also crept into
ops without this trait although they did not require it. Handle this
case earlier in the interpreter and homogeneously associated preivously
unset transform dialect values (both handles and parameters) with empty
lists of the matching kind. Ignore the results of `applyToEach` for the
targets for which it produced a silenceable failure. As a result, one
never needs to set results to lists containing nulls. Furthermore, the
objects associated with transform dialect values must never be null.
Depends On D140980
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D141305
This patch made a minor refactor of LoopCoalescing.cpp's walkLoops
templated method and placed it in Affine's LoopUtils.cpp/h.
This method is also renamed as coalescePerfectlyNestedLoops method. This
minor change enables this method to be invoked
by both the original LoopCoalescing pass as well as the newly introduced
loop.coalesce transform op.
The loop.coalesce transform op has the ability to coalesce affine, and
scf loop nests, leveraging existing LoopCoalescing
mechanism. I have created it inside the SCFTransformOps.td instead of
AffineTransformOps.td as it feels to be similar
in spirit as the loop.unroll op that can handle both scf and affine
loops. Please let me know if you feel that this op
should be moved into AffineTransformOps.td instead.
The testcase added illustrates loop.coalesce transform op working for
scf, affine loops (inner, outer) as well as
coalesced loop can be further unrolled (achieving composibility).
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D141202
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
Now we have more convenient functions to construct silenceable errors
while emitting diagnostics, and the constructor is ambiguous as it
doesn't tell whether the logical error is silencebale or definite.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D137257
mlir/lib/Dialect/SCF/TransformOps/SCFTransformOps.cpp(42): error C2446: ':': no conversion from 'OpTy' to 'OpTy'
with
[
OpTy=mlir::scf::ForOp
]
and
[
OpTy=mlir::AffineForOp
]
mlir/lib/Dialect/SCF/TransformOps/SCFTransformOps.cpp(42): note: No user-defined-conversion operator available that can perform this conversion, or the operator cannot be called
This patch consolidates the two transform ops from the affine dialect
and the scf dialect to avoid code duplication.
This is to address the review comments from
https://reviews.llvm.org/D137997.
The transform ops directory / file structure for the affine dialect is
kept for the purpose of forth-coming transform ops
for affine, but get_parent_for and unroll are removed.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D138980
The transform.split_handles op is useful for ensuring a statically known number of operations are
tracked by the source `handle` and to extract them into individual handles
that can be further manipulated in isolation.
In the process of making the op robust wrt to silenceable errors and the suppress mode, issues were
uncovered and fixed.
The main issue was that silenceable errors were short-circuited too early and the payloads were not
set. This resulted in suppressed silenceable errors not propagating correctly.
Fixing the issue triggered a few test failures: silenceable error returns now must properly set the results state.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D135426
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
This revision revisits the implementation of applyToOne and its handling
of recoverable errors as well as propagation of null handles.
The implementation is simplified to always require passing a vector<Operation*>
in which the results are returned, resulting in less template instantiation magic.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D129185
This aligns the SCF dialect file layout with the majority of the dialects.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D128049
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
Introduce transform ops for "for" loops, in particular for peeling, software
pipelining and unrolling, along with a couple of "IR navigation" ops. These ops
are intended to be generalized to different kinds of loops when possible and
therefore use the "loop" prefix. They currently live in the SCF dialect as
there is no clear place to put transform ops that may span across several
dialects, this decision is postponed until the ops actually need to handle
non-SCF loops.
Additionally refactor some common utilities for transform ops into trait or
interface methods, and change the loop pipelining to be a returning pattern.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D127300
