8 Commits

Author SHA1 Message Date
Mehdi Amini
5e118f933b Introduce MLIR Op Properties
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 d572cd1b067f after fixing python bindings build.

Differential Revision: https://reviews.llvm.org/D141742
2023-05-01 23:16:34 -07:00
Mehdi Amini
1e853421a4 Revert "Introduce MLIR Op Properties"
This reverts commit d572cd1b067f1177a981a4711bf2e501eaa8117b.

Some bots are broken and investigation is needed before relanding.
2023-05-01 15:55:58 -07:00
Mehdi Amini
d572cd1b06 Introduce MLIR Op Properties
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
2023-05-01 15:35:48 -07:00
Krzysztof Drewniak
75bfc6f295 [mlir][Arith] Implement InferIntRangeInterface for arithmetic ops
Depends on D124023

Reviewed By: Mogball, rriddle

Differential Revision: https://reviews.llvm.org/D124022
2022-06-14 18:30:34 +00:00
Mogball
ee70039ae2 [mlir] Fix handling of some region branch terminator successors
When `RegionBranchOpInterface::getSuccessorRegions` is called for anything other than the parent op, it expects the operands of the terminator of the source region to be passed, not the operands of the parent op. This was not always respected.

This fixes a bug in integer range inference and ForwardDataFlowSolver and changes `scf.while` to allow narrowing of successors using constant inputs.

Fixes #55873

Reviewed By: mehdi_amini, krzysz00

Differential Revision: https://reviews.llvm.org/D127261
2022-06-08 17:17:03 +00:00
Krzysztof Drewniak
95aff23e29 Re-land "[mlir] Add integer range inference analysis""
This reverts commit 4e5ce2056e3e85f109a074e80bdd23a10ca2bed9.

This relands commit 1350c9887dca5ba80af8e3c1e61b29d6696eb240.

Reinstates the range analysis with the build issue fixed.

Differential Revision: https://reviews.llvm.org/D126926
2022-06-03 17:13:48 +00:00
Mehdi Amini
4e5ce2056e Revert "[mlir] Add integer range inference analysis"
This reverts commit 1350c9887dca5ba80af8e3c1e61b29d6696eb240.

Shared library build is broken with undefined references.
2022-06-02 21:24:06 +00:00
Krzysztof Drewniak
1350c9887d [mlir] Add integer range inference analysis
This commit defines a dataflow analysis for integer ranges, which
uses a newly-added InferIntRangeInterface to compute the lower and
upper bounds on the results of an operation from the bounds on the
arguments. The range inference is a flow-insensitive dataflow analysis
that can be used to simplify code, such as by statically identifying
bounds checks that cannot fail in order to eliminate them.

The InferIntRangeInterface has one method, inferResultRanges(), which
takes a vector of inferred ranges for each argument to an op
implementing the interface and a callback allowing the implementation
to define the ranges for each result. These ranges are stored as
ConstantIntRanges, which hold the lower and upper bounds for a
value. Bounds are tracked separately for the signed and unsigned
interpretations of a value, which ensures that the impact of
arithmetic overflows is correctly tracked during the analysis.

The commit also adds a -test-int-range-inference pass to test the
analysis until it is integrated into SCCP or otherwise exposed.

Finally, this commit fixes some bugs relating to the handling of
region iteration arguments and terminators in the data flow analysis
framework.

Depends on D124020

Depends on D124021

Reviewed By: rriddle, Mogball

Differential Revision: https://reviews.llvm.org/D124023
2022-06-02 20:24:11 +00:00