This change adds a builder that populates the body of a SequenceOp. This is useful for constructing SequenceOps from C++.
Differential Revision: https://reviews.llvm.org/D137710
This op dumps the associated payload IR to stderr. It has proven useful for printf-style debugging.
Differential Revision: https://reviews.llvm.org/D137151
This class adds helper functions similar to `emitError` for the
DiagnosedSilenceableFailure class in both the silenceable and definite
failure cases. These helpers simplify the use of said class and make
tranfsorm op application code idiomatic.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D136072
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 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
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
The op was declaring the effects associated with payload IR as attached
to its operand since ODS doesn't allow otherwise. Implement the memory
effects query method in C++ instead to make the effect not attached to
the operand.
Relax the restriction in the transform dialect interpreter utilities
that expected a payload IR op to be assocaited with at most one
transform IR handle value. This was useful during the initial
bootstrapping to avoid use-after-free error equivalents when a payload
IR op could be erased through one of the handles associated with it and
then accessed through another. It was, however, possible to erase an
ancestor of the payload IR operation in question. The expensive-checks
mode of interpretation is able to detect both cases and has proven
sufficiently robust in debugging use-after-free errors.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D134964
Given an opOperand uniquely determined by the operation `%op` and the operand number `num`,
the `transform.get_producer_of_operand %op[num]` returns the handle to the unique operation
that produced the SSA value used as opOperand.
The transform fails if the operand is a block argument.
Differential Revision: https://reviews.llvm.org/D134171
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
A recent commit introduced helper functions with semantically meaningful names
to populate the lists of memory effects in transform ops, use them whenever
possible.
Depends On D129287
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D129365
This handle manipulation operation allows one to define a new handle that is
associated with a the same payload IR operations N times, where N can be driven
by the size of payload IR operation list associated with another handle. This
can be seen as a sort of broadcast that can be used to ensure the lists
associated with two handles have equal numbers of payload IR ops as expected by
many pairwise transform operations.
Introduce an additional "expensive" check that guards against consuming a
handle that is assocaited with the same payload IR operation more than once as
this is likely to lead to double-free or other undesired effects.
Depends On D129110
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D129216
This Transform dialect op allows one to merge the lists of Payload IR
operations pointed to by several handles into a single list associated with one
handle. This is an important Transform dialect usability improvement for cases
where transformations may temporarily diverge for different groups of Payload
IR ops before converging back to the same script. Without this op, several
copies of the trailing transformations would have to be present in the
transformation script.
Depends On D129090
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D129110
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
Ops that implement `RegionBranchOpInterface` are allowed to indicate that they can branch back to themselves in `getSuccessorRegions`, but there is no API that allows them to specify the forwarded operands. This patch enables that by changing `getSuccessorEntryOperands` to accept `None`.
Fixes#54928
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D127239
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
Vectorization is a key transformation to achieve high performance on most
architectures. In the transform dialect, vectorization is implemented as a
parameterizable transform op. It currently applies to a scope of payload IR
delimited by some isolated-from-above op, mainly because several enabling
transformations (such as affine simplification) are needed to perform
vectorization and these transformation would apply to ops other than the "main"
computational payload op. A separate "navigation" transform op that obtains the
isolated-from-above ancestor of an op is introduced in the core transform
dialect. Even though it is currently only useful for vectorization,
isolated-from-above ops are a common anchor for transformations (usually
implemented as passes) that is likely to be reused in the future.
Depends On D126374
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D126542
The Transform dialect uses the side effect modeling mechanism to record the
effects of the transform ops on the mapping between Transform IR values and
Payload IR ops. Introduce a checker pass that warns if a Transform IR value is
used after it has been freed (consumed). This pass is mostly intended as a
debugging aid in addition to the verification/assertion mechanisms in the
transform interpreter. It reports all potential use-after-free situations.
The implementation makes a series of simplifying assumptions to be simple and
conservative. A more advanced implementation would rely on the data flow-like
analysis associated with a side-effect resource rather than a value, which is
currently not supported by the analysis infrastructure.
Reviewed By: springerm
Differential Revision: https://reviews.llvm.org/D126381
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
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
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
