The current translation uses the old "ugly"/"raw" form which used PDLValue for the arguments
and results. This commit updates the C++ generation to use the recently added sugar that
allows for directly using the desired types for the arguments and result of PDL functions.
In addition, this commit also properly imports the C++ class for ODS operations, constraints,
and interfaces. This allows for a much more convienent C++ API than previously granted
with the raw/low-level types.
Differential Revision: https://reviews.llvm.org/D124817
If we don't specify the result index while matching operand with the
result of certain operation, it's supposed to match all the results of
the operation with the operand. For registered op, it's easy to do that
by either indexing with number or name. For unregistered op, this commit
enables the numeric result indexing for this use case.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D126330
This support has never really worked well, and is incredibly clunky to
use (it effectively creates two argument APIs), and clunky to generate (it isn't
clear how we should actually expose this from PDL frontends). Treating these
as just attribute arguments is much much cleaner in every aspect of the stack.
If we need to optimize lots of constant parameters, it would be better to
investigate internal representation optimizations (e.g. batch attribute creation),
that do not affect the user (we want a clean external API).
Differential Revision: https://reviews.llvm.org/D121569
There is no reason for this file to be at the top-level, and
its current placement predates the Parser/ folder's existence.
Differential Revision: https://reviews.llvm.org/D121024
This commit adds support for processing tablegen include files, and importing
various information from ODS. This includes operations, attribute+type constraints,
attribute/operation/type interfaces, etc. This will allow for much more robust tooling,
and also allows for referencing ODS constructs directly within PDLL (imported interfaces
can be used as constraints, operation result names can be used for member access, etc).
Differential Revision: https://reviews.llvm.org/D119900
This commits starts to plumb PDLL down into MLIR and adds an initial
PDL generator. After this commit, we will have conceptually support
end-to-end execution of PDLL. Followups will add CPP generation to
match the current DRR setup, and begin to add various end-to-end
tests to test PDLL execution.
Differential Revision: https://reviews.llvm.org/D119779
