Data layout queries may be issued for types whose size exceeds the range
of 32-bit integer as well as for types that don't have a size known at
compile time, such as scalable vectors. Use best practices from LLVM IR
and adopt `llvm::TypeSize` for size-related queries and `uint64_t` for
alignment-related queries.
See #72678.
In #71153, the `memref.subview` canonicalizer crashes due to a negative
`size` being passed as an operand. During `SubViewOp::verify` this
negative `size` is not yet detectable since it is dynamic and only
available after constant folding, which happens during the
canonicalization passes. As discussed in
<https://discourse.llvm.org/t/rfc-more-opfoldresult-and-mixed-indices-in-ops-that-deal-with-shaped-values/72510>,
the verifier should not be extended as it should "only verify local
aspects of an operation".
This patch fixes#71153 by not folding in aforementioned situation.
Also, this patch adds a basic offset and size check in the
`OffsetSizeAndStrideOpInterface` verifier.
Note: only `offset` and `size` are checked because `stride` is allowed
to be negative
(54d81e49e3).
The majority of subset ops operate on hyperrectangular subsets. This
commit adds a new optional interface method
(`getAccessedHyperrectangularSlice`) that can be implemented by such
subset ops. If implemented, the other `operatesOn...` interface methods
of the `SubsetOpInterface` do not have to be implemented anymore.
The comparison logic for hyperrectangular subsets (is
disjoint/equivalent) is implemented with `ValueBoundsOpInterface`. This
makes the subset hoisting more powerful: simple cases where two
different SSA values always have the same runtime value can now be
supported.
There is currently an op interface for subset insertion ops
(`SubsetInsertionOpInterface`), but not for subset extraction ops. This
commit adds `SubsetExtractionOpInterface` to `mlir/Interfaces`, as well
as a common dependent op interface: `SubsetOpInterface`.
- `SubsetOpInterface` is for ops that operate on tensor subsets. It
provides interface methods to check if two subset ops operate on
equivalent or disjoint subsets. Ops that implement this interface must
implement either `SubsetExtractionOpInterface` or
`SubsetInsertionOpInterface`.
- `SubsetExtractionOpInterface` is for ops that extract from a tensor at
a subset. E.g., `tensor.extract_slice`, `tensor.gather`,
`vector.transfer_read`. Current implemented only on
`tensor.extract_slice`.
- `SubsetInsertionOpInterface` is for ops that insert into a destination
tensor at a subset. E.g., `tensor.insert_slice`,
`tensor.parallel_insert_slice`, `tensor.scatter`,
`vector.transfer_write`. Currently only implemented on
`tensor.insert_slice`, `tensor.parallel_insert_slice`.
Other changes:
- Rename `SubsetInsertionOpInterface.td` to `SubsetOpInterface.td`.
- Add helper functions to `ValueBoundsOpInterface.cpp` for checking
whether two slices are disjoint.
The new interfaces will be utilized by a new "loop-invariant subset
hoisting"
transformation. (This new transform is roughly
what `Linalg/Transforms/SubsetHoisting.cpp` is doing, but in a generic
and interface-driven way.)
Expose loop results, which correspond to the region iter_arg values that
are returned from the loop when there are no more iterations. Exposing
loop results is optional because some loops (e.g., `scf.while`) do not
have a 1-to-1 mapping between region iter_args and op results.
Also add additional helper functions to query tied
results/iter_args/inits.
`SubsetInsertionOpInterface` is an interface for ops that insert into a
destination tensor at a subset. It is currently used by the
bufferization framework to support efficient
`tensor.extract_slice/insert_slice` bufferization and to drive "empty
tensor elimination".
This commit moves the interface to `mlir/Interfaces`. This is in
preparation of adding a new "loop-invariant subset hoisting"
transformation to
`mlir/Transforms/Utils/LoopInvariantCodeMotionUtils.cpp`, which will
utilize `SubsetInsertionOpInterface`. (This new transform is roughly
what `Linalg/Transforms/SubsetHoisting.cpp` is doing, but in a generic
and interface-driven way.)
Add a new interface method that returns the yielded values.
Also add a verifier that checks the number of inits/iter_args/yielded
values. Most of the checked invariants (but not all of them) are already
covered by the `RegionBranchOpInterface`, but the `LoopLikeOpInterface`
now provides (additional) error messages that are easier to read.
Recent changes (https://github.com/llvm/llvm-project/pull/66930)
disabled vector transfer ops hoisting with view-like intermediate ops.
The recommended way is to fold subview ops into transfer op indices
before invoking hoisting. That would mean now we see transfer op indices
involving dynamic values, instead of static constant values before with
subview ops. Therefore hoisting won't kick in anymore. This breaks
downstream users.
To fix it, this commit enables hoisting transfer ops with dynamic
indices by using `ValueBoundsConstraintSet` to prove ranges are disjoint
in `isDisjointTransferIndices`. Given that utility is used in many
places including op folders, right now we introduce a flag to it and
only set as true for "heavy" transforms in hoisting and load-store
forwarding.
* "init" operands are specified with `MutableOperandRange` (which gives
access to the underlying `OpOperand *`). No more magic numbers.
* Remove most interface methods and make them helper functions. Only
`getInitsMutable` should be implemented.
* Provide separate helper functions for accessing mutable/immutable
operands (`OpOperand`/`Value`, in line with #66515): `getInitsMutable`
and `getInits` (same naming convention as auto-generated op accessors).
`getInputOperands` was not renamed because this function cannot return a
`MutableOperandRange` (because the operands are not necessarily
consecutive). `OpOperandVector` is no longer needed.
* The new `getDpsInits`/`getDpsInitsMutable` is more efficient than the
old `getDpsInitOperands` because no `SmallVector` is created. The new
functions return a range of operands.
* Fix a bug in `getDpsInputOperands`: out-of-bounds operands were
potentially returned.
This commit provides a default implementation for all ops that implement
the `DestinationStyleOpInterface`. Result values of such ops are tied to
operand, and those have the same type.
Functions are always callable operations and thus every operation
implementing the `FunctionOpInterface` also implements the
`CallableOpInterface`. The only exception was the FuncOp in the toy
example. To make implementation of the `FunctionOpInterface` easier,
this commit lets `FunctionOpInterface` inherit from
`CallableOpInterface` and merges some of their methods. More precisely,
the `CallableOpInterface` has methods to get the argument and result
attributes and a method to get the result types of the callable region.
These methods are always implemented the same way as their analogues in
`FunctionOpInterface` and thus this commit moves all the argument and
result attribute handling methods to the callable interface as well as
the methods to get the argument and result types. The
`FuntionOpInterface` then does not have to declare them as well, but
just inherits them from the `CallableOpInterface`.
Adding the inheritance relation also required to move the
`FunctionOpInterface` from the IR directory to the Interfaces directory
since IR should not depend on Interfaces.
Reviewed By: jpienaar, springerm
Differential Revision: https://reviews.llvm.org/D157988
The current implementation is not very ergonomic or descriptive: It uses `std::optional<unsigned>` where `std::nullopt` represents the parent op and `unsigned` is the region number.
This doesn't give us any useful methods specific to region control flow and makes the code fragile to changes due to now taking the region number into account.
This patch introduces a new type called `RegionBranchPoint`, replacing all uses of `std::optional<unsigned>` in the interface. It can be implicitly constructed from a region or a `RegionSuccessor`, can be compared with a region to check whether the branch point is branching from the parent, adds `isParent` to check whether we are coming from a parent op and adds `RegionSuccessor::parent` as a descriptive way to indicate branching from the parent.
Differential Revision: https://reviews.llvm.org/D159116
The verifier incorrectly passed the region number of the predecessor region instead of the successor region to `getSuccessorOperands`. This went unnoticed since all upstream `RegionBranchTerminatorOpInterface` implementations did not make use of the `index` parameter.
Adding an assert to e.g. `scf.condition` to make sure the index is valid or adding a region terminator that passes different operands to different successors immediately causes the verifier to fail as it suddenly gets incorrect types.
This patch fixes the implementation to correctly pass the successor region index.
Differential Revision: https://reviews.llvm.org/D157507
Add support for reasoning about operations with recursive memory effects
to CSE. The recursive effects are gathered by a helper function. I
decided to allow returning duplicates from the helper function because
there's no benefit to spending the computation time to remove them in
the existing use case.
Differential Revision: https://reviews.llvm.org/D156805
The `RegionBranchOpInterface` had a few fundamental issues caused by the API design of `getSuccessorRegions`.
It always required passing values for the `operands` parameter. This is problematic as the operands parameter actually changes meaning depending on which predecessor `index` is referring to. If coming from a region, you'd have to find a `RegionBranchTerminatorOpInterface` in that region, get its operand count, and then create a `SmallVector` of that size.
This is not only inconvenient, but also error-prone, which has lead to a bug in the implementation of a previously existing `getSuccessorRegions` overload.
Additionally, this made the method dual-use, trying to serve two different use-cases: 1) Trying to determine possible control flow edges between regions and 2) Trying to determine the region being branched to based on constant operands.
This patch fixes these issues by changing the interface methods and adding new ones:
* The `operands` argument of `getSuccessorRegions` has been removed. The method is now only responsible for returning possible control flow edges between regions.
* An optional `getEntrySuccessorRegions` method has been added. This is used to determine which regions are branched to from the parent op based on constant operands of the parent op. By default, it calls `getSuccessorRegions`. This is analogous to `getSuccessorForOperands` from `BranchOpInterface`.
* Add `getSuccessorRegions` to `RegionBranchTerminatorOpInterface`. This is used to get the possible successors of the terminator based on constant operands. By default, it calls the containing `RegionBranchOpInterface`s `getSuccessorRegions` method.
* `getSuccessorEntryOperands` was renamed to `getEntrySuccessorOperands` for consistency.
Differential Revision: https://reviews.llvm.org/D157506
This implication was already done de-facto and there were plenty of users and wrapper functions specifically used to handle the "return-like or RegionBranchTerminatorOpInterface" case. These simply existed due to up until recently missing features in ODS.
With the new capabilities of traits, we can make `ReturnLike` imply `RegionBranchTerminatorOpInterface` and auto generate proper definitions for its methods.
Various occurrences and wrapper methods used for `isa<RegionBranchTerminatorOpInterface>() || hasTrait<ReturnLike>()` have all been removed.
Differential Revision: https://reviews.llvm.org/D157402
Also make `getNumDynamicEntriesUpToIdx` a helper function. It does not have to be an interface method.
Differential Revision: https://reviews.llvm.org/D156864
Support extra concrete class declarations and definitions under NativeTrait that get injected into the class that specifies the trait. Extra declarations and definitions can be passed in as template arguments for NativeOpTraitNativeAttrTrait and NativeTypeTrait.
Usage examples of this feature include:
- Creating a wrapper Trait for authoring inferReturnTypes with the OpAdaptor by specifying necessary Op specific declarations and definitions directly in the trait
- Refactoring the InferTensorType trait
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D154731
This change lifts the limitation that only the trailing dimensions/sizes
in dynamic index lists can be scalable. It allows us to extend
`MaskedVectorizeOp` and `TileOp` from the Transform dialect so that the
following is allowed:
%1, %loops:3 = transform.structured.tile %0 [4, [4], [4]]
This is also a follow up for https://reviews.llvm.org/D153372
that will enable the following (middle vector dimension is scalable):
transform.structured.masked_vectorize %0 vector_sizes [2, [4], 8]
To facilate this change, the hooks for parsing and printing dynamic
index lists are updated accordingly (`printDynamicIndexList` and
`parseDynamicIndexList`, respectively). `MaskedVectorizeOp` and `TileOp`
are updated to include an array of attribute of bools that captures
whether the corresponding vector dimension/tile size, respectively, are
scalable or not.
NOTE 1: I am re-landing this after the initial version was reverted. To
fix the regression and in addition to the original patch, this revision
updates the Python bindings for the transform dialect
NOTE 2: This change is a part of a larger effort to enable scalable
vectorisation in Linalg. See this RFC for more context:
* https://discourse.llvm.org/t/rfc-scalable-vectorisation-in-linalg/
This relands 048764f23a with fixes.
Differential Revision: https://reviews.llvm.org/D154336
This change lifts the limitation that only the trailing dimensions/sizes
in dynamic index lists can be scalable. It allows us to extend
`MaskedVectorizeOp` and `TileOp` from the Transform dialect so that the
following is allowed:
%1, %loops:3 = transform.structured.tile %0 [[4], [4], 4]
This is also a follow up for https://reviews.llvm.org/D153372
that will enable the following (middle vector dimension is scalable):
transform.structured.masked_vectorize %0 vector_sizes [2, [4], 8]
To facilate this change, the hooks for parsing and printing dynamic
index lists are updated accordingly (`printDynamicIndexList` and
`parseDynamicIndexList`, respectively). `MaskedVectorizeOp` and `TileOp`
are updated to include an array of attribute of bools that captures
whether the corresponding vector dimension/tile size, respectively, are
scalable or not.
This change is a part of a larger effort to enable scalable
vectorisation in Linalg. See this RFC for more context:
* https://discourse.llvm.org/t/rfc-scalable-vectorisation-in-linalg/
Differential Revision: https://reviews.llvm.org/D154336
The greedy pattern rewrite driver removes ops that are "trivially dead". This could include symbols that are still referenced by other ops. Dead symbols should be removed with the `-symbol-dce` pass instead.
This bug was not triggered for `func::FuncOp`, because ops are not considered "trivally dead" if they do not implement the `MemoryEffectOpInterface`, indicating that the op may or may not have side effects. It is, however, triggered for `transform::NamedSequenceOp`, which implements that interface because it is required for all transform dialect ops.
Differential Revision: https://reviews.llvm.org/D152994
This patch enables specifying scalable vector sizes when using the
Transform dialect to drive vectorisation, e.g.:
```
transform.structured.masked_vectorize %0 vector_sizes [8, 16, [4]]
```
This is implemented by extending the MaskedVectorizeOp with a dedicated
attribute for "scalability" and by overloading `parseDynamicIndexList`
so that MaskedVectorizeOp can continue using the auto-generated parser
and printer.
At the moment, only the trailing vec size can be scalable. The following
is not yet supported:
```
transform.structured.masked_vectorize %0 vector_sizes [8, [16], [4]]
```
As the vectoriser does not support scalable vectorisation just yet, a
warning is issues when scalable vector sizes are used. You can also use
the debug output, `--debug-only=linalg-vectorization`, to check whether
scalable vectorisation has been switched on.
This change is a part of a larger effort to enable scalable
vectorisation in Linalg. See this RFC for more context:
* https://discourse.llvm.org/t/rfc-scalable-vectorisation-in-linalg/
Similar patch for tiling: https://reviews.llvm.org/D150944
Differential Revision: https://reviews.llvm.org/D151892
These helpers should not be part of the IR build unit.
The interface is now implemented on `builtin.unrealized_conversion_cast` with an external model.
Also rename the CastOpInterfaces Bazel target name to CastInterfaces to be consistent with the CMake target name.
Differential Revision: https://reviews.llvm.org/D146972
This patch enables specifying scalable tile sizes when using the
Transform dialect to drive tiling, e.g.:
```
%1, %loop = transform.structured.tile %0 [[4]]
```
This is implemented by extending the TileOp with a dedicated attribute
for "scalability" and by updating various parsing hooks. At the moment,
only the trailing tile size can be scalable. The following is not yet
supported:
```
%1, %loop = transform.structured.tile %0 [[4], [4]]
```
This change is a part of larger effort to enable scalable vectorisation
in Linalg. See this RFC for more context:
* https://discourse.llvm.org/t/rfc-scalable-vectorisation-in-linalg/
Differential Revision: https://reviews.llvm.org/D150944
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 patch updates all remaining uses of the deprecated functionality in
mlir/. This was done with clang-tidy as described below and further
modifications to GPUBase.td and OpenMPOpsInterfaces.td.
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:
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.
```
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
```
Differential Revision: https://reviews.llvm.org/D151542
Add a helper function that computes if two SSA values have the same value, utilizing the `ValueBoundsOpInterface` infrastructure. Two SSA values have the same value, an equality bound of 0 can be derived for their subtraction.
The helper function can also be used to determine if two tensor dimension sizes are equal.
Differential Revision: https://reviews.llvm.org/D151443
This revision introduces a generic implementation of Scalar Replacement
Of Aggregates. In contrast to the implementation in LLVM, this focuses
on the core of SROA: destructuring aggregates. By implementing
interfaces on allocators and accessors, memory allocators can be
destructured into smaller allocators, through the MemorySlot
abstraction.
This pass only works on aggregates that are accessed in a "type-safe"
way, that is within the bounds and respecting the type of a given memory
slot. The destructuring pattern and functions only peel off the first
layer of aggregates and can safely be applied repeatedly. For
convenience, the transformation is also available as a pass that will
apply the pattern repeatedly.
Depends on D149958
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D150186
Types have been introduced a while ago and provide for better
readability and transform-time verification. Use them in the ops from
the structured transform dialect extension.
In most cases, the types are appended as trailing functional types or a
derived format of the functional type that allows for an empty right
hand size without the annoying `-> ()` syntax (similarly to `func.func`
declaration that may omit the arrow). When handles are used inside mixed
static/dynamic lists, such as tile sizes, types of those handles follow
them immediately as in `sizes [%0 : !transform.any_value, 42]`. This
allows for better readability than matching the trailing type.
Update code to remove hardcoded PDL dependencies and expunge PDL from
structured transform op code.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D144515
Also some simplifications:
* `outputBufferOperands` was unused.
* The condition that the number of operands equals the number of inputs
plus the number of inits seemed vacuously true (?).
Differential Revision: https://reviews.llvm.org/D150376
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
This patch refactors the Mem2Reg infrastructure. It decouples
analysis from promotion, allowing for more control over the execution of
the logic. It also adjusts the interfaces to be less coupled to mem2reg
and more general. This will be useful for an upcoming revision
introducing generic SROA.
This commit reverts f333977eb2 and relands 91cff8a718.
The original commit was reverted accidentally due to a misinterpretation
of a bazel build bot failure.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D149825
This patch refactors the Mem2Reg infrastructure. It decouples
analysis from promotion, allowing for more control over the execution of
the logic. It also adjusts the interfaces to be less coupled to mem2reg
and more general. This will be useful for an upcoming revision
introducing generic SROA.
Reviewed By: gysit
Differential Revision: https://reviews.llvm.org/D149825
This new features enabled to dedicate custom storage inline within operations.
This storage can be used as an alternative to attributes to store data that is
specific to an operation. Attribute can also be stored inside the properties
storage if desired, but any kind of data can be present as well. This offers
a way to store and mutate data without uniquing in the Context like Attribute.
See the OpPropertiesTest.cpp for an example where a struct with a
std::vector<> is attached to an operation and mutated in-place:
struct TestProperties {
int a = -1;
float b = -1.;
std::vector<int64_t> array = {-33};
};
More complex scheme (including reference-counting) are also possible.
The only constraint to enable storing a C++ object as "properties" on an
operation is to implement three functions:
- convert from the candidate object to an Attribute
- convert from the Attribute to the candidate object
- hash the object
Optional the parsing and printing can also be customized with 2 extra
functions.
A new options is introduced to ODS to allow dialects to specify:
let usePropertiesForAttributes = 1;
When set to true, the inherent attributes for all the ops in this dialect
will be using properties instead of being stored alongside discardable
attributes.
The TestDialect showcases this feature.
Another change is that we introduce new APIs on the Operation class
to access separately the inherent attributes from the discardable ones.
We envision deprecating and removing the `getAttr()`, `getAttrsDictionary()`,
and other similar method which don't make the distinction explicit, leading
to an entirely separate namespace for discardable attributes.
Recommit d572cd1b06 after fixing python bindings build.
Differential Revision: https://reviews.llvm.org/D141742
This new features enabled to dedicate custom storage inline within operations.
This storage can be used as an alternative to attributes to store data that is
specific to an operation. Attribute can also be stored inside the properties
storage if desired, but any kind of data can be present as well. This offers
a way to store and mutate data without uniquing in the Context like Attribute.
See the OpPropertiesTest.cpp for an example where a struct with a
std::vector<> is attached to an operation and mutated in-place:
struct TestProperties {
int a = -1;
float b = -1.;
std::vector<int64_t> array = {-33};
};
More complex scheme (including reference-counting) are also possible.
The only constraint to enable storing a C++ object as "properties" on an
operation is to implement three functions:
- convert from the candidate object to an Attribute
- convert from the Attribute to the candidate object
- hash the object
Optional the parsing and printing can also be customized with 2 extra
functions.
A new options is introduced to ODS to allow dialects to specify:
let usePropertiesForAttributes = 1;
When set to true, the inherent attributes for all the ops in this dialect
will be using properties instead of being stored alongside discardable
attributes.
The TestDialect showcases this feature.
Another change is that we introduce new APIs on the Operation class
to access separately the inherent attributes from the discardable ones.
We envision deprecating and removing the `getAttr()`, `getAttrsDictionary()`,
and other similar method which don't make the distinction explicit, leading
to an entirely separate namespace for discardable attributes.
Differential Revision: https://reviews.llvm.org/D141742
