25 Commits

Author SHA1 Message Date
Oleksandr "Alex" Zinenko
5a9bdd85ee
[mlir] split transform interfaces into a separate library (#85221)
Transform interfaces are implemented, direction or via extensions, in
libraries belonging to multiple other dialects. Those dialects don't
need to depend on the non-interface part of the transform dialect, which
includes the growing number of ops and transitive dependency footprint.

Split out the interfaces into a separate library. This in turn requires
flipping the dependency from the interface on the dialect that has crept
in because both co-existed in one library. The interface shouldn't
depend on the transform dialect either.

As a consequence of splitting, the capability of the interpreter to
automatically walk the payload IR to identify payload ops of a certain
kind based on the type used for the entry point symbol argument is
disabled. This is a good move by itself as it simplifies the interpreter
logic. This functionality can be trivially replaced by a
`transform.structured.match` operation.
2024-03-20 22:15:17 +01:00
Ingo Müller
99c15eb49b
[mlir][transform] Handle multiple library preloading passes. (#69705)
This is a new attempt at #69320.

The transform dialect stores a "library module" that the preload pass
can populate. Until now, each pass registered an additional module by
simply pushing it to a vector; however, the interpreter only used the
first of them. This commit turns the registration into "loading", i.e.,
each newly added module gets merged into the existing one. This allows
the loading to be split into several passes, and using the library in
the interpreter now takes all of them into account. While this design
avoids repeated merging every time the library is accessed, it requires
that the implementation of merging modules lives in the
TransformDialect target (since it at the dialect depend on each
other).

This resolves https://github.com/llvm/llvm-project/issues/69111.
2023-10-25 09:52:30 +02:00
Matthias Springer
bcfdb3e4bc [mlir][transform] Add apply_conversion_patterns op
This transform op applies a dialect conversion to the targeted ops. Its design is similar to `apply_patterns`.

Patterns are specified in the first region of `apply_conversion_patterns`. They must implement the `ConversionPatternDescriptorOpInterface`. Regular rewrite patterns and dialect conversion patterns should not be mixed, so the interface is separate from the `PatternDescriptorOpInterface`.

The type converter is specified as the single op of the second region. It is optional; if no type converter is specified, it is expected that pattern descriptors provide their own type converters. If both the pattern descriptors and the `apply_conversion_patterns` op specify a type converter, the type converter of the pattern descriptor is used.

Differential Revision: https://reviews.llvm.org/D157109
2023-08-07 08:49:55 +02:00
Matthias Springer
c63d2b2c71 [mlir][transform] Add TransformRewriter
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
2023-06-20 10:49:59 +02:00
Matthias Springer
5a10f207cc [mlir][transform] Add region to ApplyPatternsOp
Patterns should be selected by adding ops that implement `PatternDescriptorOpInterface` to the region of `apply_pattern` ops. Such ops can have operands, allowing for pattern parameterization. The existing way of selecting patterns from the PatternRegistry is deprecated.

Differential Revision: https://reviews.llvm.org/D152167
2023-06-06 09:09:41 +02:00
Matthias Springer
60f06bc5bb [mlir][transform] ApplyPatternsOp: Register canonicalization patterns
Also support replacing payload ops with ConstantLike ops in the TrackingListener, even if the replacement op does not have the same name. (Not supported for ops with multiple results, as this would require splitting the handle.)

Differential Revision: https://reviews.llvm.org/D152127
2023-06-05 11:37:43 +02:00
Alex Zinenko
94d608d410 [mlir] move PDL-related transform ops into an extension
The initial bring-up of the Transform dialect relied on PDL to provide
the default handle type (`!pdl.operation`) and the matching capability.
Both are now provided natively by the Transform dialect removing the
reason to have a hard dependency on the PDL dialect and its interpreter.
Move PDL-related transform operations into a separate extension.

This requires us to introduce a dialect state extension mechanism into
the Transform dialect so it no longer needs to know about PDL constraint
functions that may be injected by extensions similarly to operations and
types. This mechanism will be reused to connect pattern application
drivers and the Transform dialect.

This completes the restructuring of the Transform dialect to remove
overrilance on PDL.

Note to downstreams: flow that are using `!pdl.operation` with Transform
dialect operations will now require `transform::PDLExtension` to be
applied to the transform dialect in order to provide the transform
handle type interface for `!pdl.operation`.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D151104
2023-05-24 12:25:06 +00:00
Tres Popp
c1fa60b4cd [mlir] Update method cast calls to function calls
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.

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 follows a previous patch that updated calls
`op.cast<T>()-> cast<T>(op)`. However some cases could not handle an
unprefixed `cast` call due to occurrences of variables named cast, or
occurring inside of class definitions which would resolve to the method.
All C++ files that did not work automatically with `cast<T>()` are
updated here to `llvm::cast` and similar with the intention that they
can be easily updated after the methods are removed through a
find-replace.

See https://github.com/llvm/llvm-project/compare/main...tpopp:llvm-project:tidy-cast-check
for the clang-tidy check that is used and then update printed
occurrences of the function to include `llvm::` before.

One can then run the following:
```
ninja -C $BUILD_DIR clang-tidy

run-clang-tidy -clang-tidy-binary=$BUILD_DIR/bin/clang-tidy -checks='-*,misc-cast-functions'\
                 -export-fixes /tmp/cast/casts.yaml mlir/*\
                 -header-filter=mlir/ -fix

rm -rf $BUILD_DIR/tools/mlir/**/*.inc
```

Differential Revision: https://reviews.llvm.org/D150348
2023-05-12 11:21:30 +02:00
Alex Zinenko
3fe7127d48 [mlir] add structured (Linalg) transform op matchers
Add a set of transform operations into the "structured" extension of the
Transform dialect that allow one to select transformation targets more
specifically than the currently available matching. In particular, add
the mechanism for identifying the producers of operands (input and init
in destination-passing style) and users of results, as well as
mechanisms for reasoning about the shape of the iteration space.

Additionally, add several transform operations to manipulate parameters
that could be useful to implement more advanced selectors. Specifically,
new operations let one produce and compare parameter values to implement
shape-driven transformations.

New operations are placed in separate files to decrease compilation
time. Some relayering of the extension is necessary to avoid repeated
generation of enums.

Depends on D148013
Depends on D148014
Depends on D148015

Reviewed By: chelini

Differential Revision: https://reviews.llvm.org/D148017
2023-04-13 12:37:51 +00:00
Alex Zinenko
4110934120 [mlir] add readonly/consume annotations to transform named sequences
Use the argument attribute mechanism for function-like operations to
annotate the arguments of named transform sequences as consuming or only
reading the handles passed as arguments. This makes it possible to
correctly specify handle invalidation for external named sequences by
requiring their declarations to always provide such annotations.
Additionally, these annotations remove the need to analyze the body of
a named sequence to understand its effects on the arguments. Make them
required for named sequences that are called from the same file, in
addition to external sequences.

Provide a convenience pass that infers annotations by analyzing bodies
of named sequences provided they are not called from the same file.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D147223
2023-04-04 09:38:00 +00:00
Alex Zinenko
fb409a2822 [mlir] Transform dialect: add named sequences
Named sequences introduce an additional abstraction and reuse capability
to the transform dialect. They can be though of as macros parameterized
with handles that can be invoked in places where a transform dialect
operation is expected. Such reuse was previously not possible in the
dialect and required dynamic construction of the transform IR from the
client language. Named sequences are intentionally restricted to
disallow recursion, as it could make the dialect accidentally
Turing-complete, which isn't desired at this point.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D146433
2023-03-21 14:53:54 +00:00
Alex Zinenko
a702628843 [mlir] add support for transform dialect value handles
Introduce support for the third kind of values in the transform dialect:
value handles. Similarly to operation handles, value handles are
pointing to a set of values in the payload IR. This enables
transformation to be targeted at specific values, such as individual
results of a multi-result payload operation without indirecting through
the producing op or block arguments that previously could not be easily
addressed. This is expected to support a broad class of memory-oriented
transformations such as selective bufferization, buffer assignment, and
memory transfer management.

Value handles are functionally similar to operation handles and require
similar implementation logic. The most important change concerns the
handle invalidation mechanism where operation and value handles can
affect each other.

This patch includes two cleanups that make it easier to introduce value
handles:

  - `RaggedArray` structure that encapsulates the SmallVector of
    ArrayRef backed by flat SmallVector logic, frequently used in the
    transform interfaces implementation;

  - rewrite the tests that associated payload handles with an integer
    value `reinterpret_cast`ed as a pointer, which were a frequent
    source of confusion and crashes when adding more debugging
    facilities that can inspect the payload.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D143385
2023-02-09 12:11:24 +00:00
Piotr Fusik
898b5c9f5e [NFC] Fix "form/from" typos
Reviewed By: #libc, ldionne

Differential Revision: https://reviews.llvm.org/D142007
2023-01-22 20:05:51 +01:00
Alex Zinenko
97c05062af [mlir] NFC: rename TransformTypeInterface to TransformHandleTypeInterface
This makes it more consistent with the recently added
TransformParamTypeInterface.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D140977
2023-01-06 12:23:33 +00:00
Alex Zinenko
ed02fa81fd [mlir] introduce parameters into the transofrm dialect
Introduce a new kind of values into the transform dialect -- parameter
values. These values have a type implementing the new
`TransformParamTypeInterface` and are associated with lists of
attributes rather than lists of payload operations. This mechanism
allows one to wrap numeric calculations, typically heuristics, into
transform operations separate from those at actually applying the
transformation. For example, tile size computation can be now separated
from tiling itself, and not hardcoded in the transform dialect. This
further improves the separation of concerns between transform choice and
implementation.

Reviewed By: springerm

Differential Revision: https://reviews.llvm.org/D140976
2023-01-06 12:23:29 +00:00
Alex Zinenko
3e1f6d02f7 [mlir] add OperationType to the Transform dialect
Add a new OperationType handle type to the Transform dialect. This
transform type is parameterized by the name of the payload operation it
can point to. It is intended as a constraint on transformations that are
only applicable to a specific kind of payload operations. If a
transformation is applicable to a small set of operation classes, it can
be wrapped into a transform op by using a disjunctive constraint, such
as `Type<Or<[Transform_ConcreteOperation<"foo">.predicate,
Transform_ConcreteOperation<"bar">.predicate]>>` for its operand without
modifying this type. Broader sets of accepted operations should be
modeled as specific types.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D135586
2022-10-11 09:55:19 +00:00
Alex Zinenko
6fe0309602 [mlir] switch transform dialect ops to use TransformTypeInterface
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
2022-10-11 09:55:13 +00:00
Alex Zinenko
b586d56c7b [mlir] clean up transform dialect definitions, NFC
Refactor the definition of the Transform dialect to move non-trivial
method implementations out of the .td file, and detemplatize functions
when possible while moving their implementations to a .cpp.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D135165
2022-10-11 09:55:10 +00:00
Alex Zinenko
bba85ebdfe [mlir] add types to the transform dialect
Introduce a type system for the transform dialect. A transform IR type
captures the expectations of the transform IR on the payload IR
operations that are being transformed, such as being of a certain kind
or implementing an interface that enables the transformation. This
provides stricter checking and better readability of the transform IR
than using the catch-all "handle" type.

This change implements the basic support for a type system amendable to
dialect extensions and adds a drop-in replacement for the unrestricted
"handle" type. The actual switch of transform dialect ops to that type
will happen in a separate commit.

See https://discourse.llvm.org/t/rfc-type-system-for-the-transform-dialect/65702

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D135164
2022-10-11 09:55:07 +00:00
Alex Zinenko
a60ed95419 [mlir][transform] failure propagation mode in sequence
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
2022-08-12 15:31:22 +00:00
River Riddle
eda6f907d2 [mlir][NFC] Shift a bunch of dialect includes from the .h to the .cpp
Now that dialect constructors are generated in the .cpp file, we can
drop all of the dependent dialect includes from the .h file.

Differential Revision: https://reviews.llvm.org/D124298
2022-04-23 01:09:29 -07:00
Alex Zinenko
40a8bd635b [mlir] use side effects in the Transform dialect
Currently, the sequence of Transform dialect operations only supports a single
use of each operand (verified by the `transform.sequence` operation). This was
originally motivated by the need to guard against accessing a payload IR
operation associated with a transform IR value after this operation has likely
been rewritten by a transformation. However, not all Transform dialect
operations rewrite payload IR, in particular the "navigation" operation such as
`transform.pdl_match` do not.

Introduce memory effects to the Transform dialect operations to describe their
effect on the payload IR and the mapping between payload IR opreations and
transform IR values. Use these effects to replace the single-use rule, allowing
repeated reads and disallowing use-after-free, where operations with the "free"
effect are considered to "consume" the transform IR value and rewrite the
corresponding payload IR operations). As an additional improvement, this
enables code motion transformation on the transform IR itself.

Reviewed By: Mogball

Differential Revision: https://reviews.llvm.org/D124181
2022-04-22 23:29:11 +02:00
Alex Zinenko
30f22429d3 [mlir] Connect Transform dialect to PDL
This introduces a pair of ops to the Transform dialect that connect it to PDL
patterns. Transform dialect relies on PDL for matching the Payload IR ops that
are about to be transformed. For this purpose, it provides a container op for
patterns, a "pdl_match" op and transform interface implementations that call
into the pattern matching infrastructure.

To enable the caching of compiled patterns, this also provides the extension
mechanism for TransformState. Extensions allow one to store additional
information in the TransformState and thus communicate it between different
Transform dialect operations when they are applied. They can be added and
removed when applying transform ops. An extension containing a symbol table in
which the pattern names are resolved and a pattern compilation cache is
introduced as the first client.

Depends On D123664

Reviewed By: Mogball

Differential Revision: https://reviews.llvm.org/D124007
2022-04-21 16:23:10 +02:00
Alex Zinenko
0eb403ad1b [mlir][transform] Introduce transform.sequence op
Sequence is an important transform combination primitive that just indicates
transform ops being applied in a row. The simplest version requires fails
immediately if any transformation in the sequence fails. Introducing this
operation allows one to start placing transform IR within other IR.

Depends On D123135

Reviewed By: Mogball, rriddle

Differential Revision: https://reviews.llvm.org/D123664
2022-04-19 21:41:02 +02:00
Alex Zinenko
d064c4801c [mlir] Introduce Transform dialect
This dialect provides operations that can be used to control transformation of
the IR using a different portion of the IR. It refers to the IR being
transformed as payload IR, and to the IR guiding the transformation as
transform IR.

The main use case for this dialect is orchestrating fine-grain transformations
on individual operations or sets thereof. For example, it may involve finding
loop-like operations with specific properties (e.g., large size) in the payload
IR, applying loop tiling to those and only those operations, and then applying
loop unrolling to the inner loops produced by the previous transformations. As
such, it is not intended as a replacement for the pass infrastructure, nor for
the pattern rewriting infrastructure. In the most common case, the transform IR
will be processed and applied to payload IR by a pass. Transformations
expressed by the transform dialect may be implemented using the pattern
infrastructure or any other relevant MLIR component.

This dialect is designed to be extensible, that is, clients of this dialect are
allowed to inject additional operations into this dialect using the newly
introduced in this patch `TransformDialectExtension` mechanism. This allows the
dialect to avoid a dependency on the implementation of the transformation as
well as to avoid introducing dialect-specific transform dialects.

See https://discourse.llvm.org/t/rfc-interfaces-and-dialects-for-precise-ir-transformation-control/60927.

Reviewed By: nicolasvasilache, Mogball, rriddle

Differential Revision: https://reviews.llvm.org/D123135
2022-04-14 13:48:45 +02:00