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
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
Add method to set a desired bytecode file format to generate. Change
write method to be able to return status including the minimum bytecode
version needed by reader. This enables generating an older version of
the bytecode (not dialect ops, attributes or types). But this does not
guarantee that an older version can always be generated, e.g., if a
dialect uses a new encoding only available at later bytecode version.
This clamps setting to at most current version.
Differential Revision: https://reviews.llvm.org/D146555
A dialect can opt-in to handle versioning through the
`BytecodeDialectInterface`. Few hooks are exposed to the dialect to allow
managing a version encoded into the bytecode file. The version is loaded
lazily and allows to retrieve the version information while parsing the input
IR, and gives an opportunity to each dialect for which a version is present
to perform IR upgrades post-parsing through the `upgradeFromVersion` method.
Custom Attribute and Type encodings can also be upgraded according to the
dialect version using readAttribute and readType methods.
There is no restriction on what kind of information a dialect is allowed to
encode to model its versioning. Currently, versioning is supported only for
bytecode formats.
Reviewed By: rriddle, mehdi_amini
Differential Revision: https://reviews.llvm.org/D143647
Resources are encoded in two separate sections similarly to
attributes/types, one for the actual data and one for the data
offsets. Unlike other sections, the resource sections are optional
given that in many cases they won't be present. For testing,
bytecode serialization is added for DenseResourceElementsAttr.
Differential Revision: https://reviews.llvm.org/D132729
Some tests still pass even though we don't claim big-endian support. Using
UNSUPPORTED is a better indicator than XFAIL that we don't guarantee that
the tests work.
This commit adds a new bytecode serialization format for MLIR.
The actual serialization of MLIR to binary is relatively straightforward,
given the very very general structure of MLIR. The underlying basis for
this format is a variable-length encoding for integers, which gets heavily
used for nearly all aspects of the encoding (given that most of the encoding
is just indexing into lists).
The format currently does not provide support for custom attribute/type
serialization, and thus always uses an assembly format fallback. It also
doesn't provide support for resources. These will be added in followups,
the intention for this patch is to provide something that supports the
basic cases, and can be built on top of.
https://discourse.llvm.org/t/rfc-a-binary-serialization-format-for-mlir/63518
Differential Revision: https://reviews.llvm.org/D131747
