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2023-07-28Add support for versioning properties in MLIR bytecodeMatteo Franciolini
[mlir] Add support for custom readProperties/writeProperties methods. Currently, operations that opt-in to adopt properties will see auto-generated readProperties/writeProperties methods to emit and parse bytecode. If a dialects opts in to use `usePropertiesForAttributes`, those definitions will be generated for the current definition of the op without the possibility to handle attribute versioning. The patch adds the capability for an operation to define its own read/write methods for the encoding of properties so that versioned operations can handle upgrading properties encodings. In addition to this, the patch adds an example showing versioning on NamedProperties through the dialect version API exposed by the reader. Reviewed By: mehdi_amini Differential Revision: https://reviews.llvm.org/D155340
2023-06-23Fix bytecode reader/writer on big-endian platformsUlrich Weigand
This makes the bytecode reader/writer work on big-endian platforms. The only problem was related to encoding of multi-byte integers, where both reader and writer code make implicit assumptions about endianness of the host platform. This fixes the current test failures on s390x, and in addition allows to remove the UNSUPPORTED markers from all other bytecode-related test cases - they now also all pass on s390x. Also adding a GFAIL_SKIP to the MultiModuleWithResource unit test, as this still fails due to an unrelated endian bug regarding decoding of external resources. Differential Revision: https://reviews.llvm.org/D153567 Reviewed By: mehdi_amini, jpienaar, rriddle
2023-05-31[mlir][bytecode] Error if requested bytecode version is unsupportedKevin Gleason
Currently desired bytecode version is clamped to the maximum. This allows requesting bytecode versions that do not exist. We have added callsite validation for this in StableHLO to ensure we don't pass an invalid version number, probably better if this is managed upstream. If a user wants to use the current version, then omitting `setDesiredBytecodeVersion` is the best way to do that (as opposed to providing a large number). Adding this check will also properly error on older version numbers as we increment the minimum supported version. Silently claming on minimum version would likely lead to unintentional forward incompatibilities. Separately, due to bytecode version being `int64_t` and using methods to read/write uints, we can generate payloads with invalid version numbers: ``` mlir-opt file.mlir --emit-bytecode --emit-bytecode-version=-1 | mlir-opt <stdin>:0:0: error: bytecode version 18446744073709551615 is newer than the current version 5 ``` This is fixed with version bounds checking as well. Reviewed By: mehdi_amini Differential Revision: https://reviews.llvm.org/D151838
2023-05-01Introduce MLIR Op PropertiesMehdi Amini
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
2023-05-01Revert "Introduce MLIR Op Properties"Mehdi Amini
This reverts commit d572cd1b067f1177a981a4711bf2e501eaa8117b. Some bots are broken and investigation is needed before relanding.
2023-05-01Introduce MLIR Op PropertiesMehdi Amini
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
2023-04-29[mlir][bytecode] Allow client to specify a desired version.Jacques Pienaar
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
2023-03-10Implements MLIR Bytecode versioning capabilityMatteo Franciolini
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