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llvm-project/mlir/unittests/CMakeLists.txt

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Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
set_target_properties(MLIRUnitTests PROPERTIES FOLDER "MLIR Tests")
function(add_mlir_unittest test_dirname)
add_unittest(MLIRUnitTests ${test_dirname} ${ARGN})
endfunction()
[MLIR] Exact integer emptiness checks for FlatAffineConstraints This patch adds the capability to perform exact integer emptiness checks for FlatAffineConstraints using the General Basis Reduction algorithm (GBR). Previously, only a heuristic was available for emptiness checks, which was not guaranteed to always give a conclusive result. This patch adds a `Simplex` class, which can be constructed using a `FlatAffineConstraints`, and can find an integer sample point (if one exists) using the GBR algorithm. Additionally, it adds two classes `Matrix` and `Fraction`, which are used by `Simplex`. The integer emptiness check functionality can be accessed through the new `FlatAffineConstraints::isIntegerEmpty()` function, which runs the existing heuristic first and, if that proves to be inconclusive, runs the GBR algorithm to produce a conclusive result. Differential Revision: https://reviews.llvm.org/D80860
2020-07-02 21:48:18 +08:00
add_subdirectory(Analysis)
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
add_subdirectory(Dialect)
Rework ExecutionEngine::invoke() to make it more friendly to use from C++ This new invoke will pack a list of argument before calling the `invokePacked` method. It accepts returned value as output argument wrapped in `ExecutionEngine::Result<T>`, and delegate the packing of arguments to a trait to allow for customization for some types. Reviewed By: ftynse Differential Revision: https://reviews.llvm.org/D95961
2021-02-06 09:32:40 +08:00
add_subdirectory(ExecutionEngine)
[mlir] Introduce data layout modeling subsystem Data layout information allows to answer questions about the size and alignment properties of a type. It enables, among others, the generation of various linear memory addressing schemes for containers of abstract types and deeper reasoning about vectors. This introduces the subsystem for modeling data layouts in MLIR. The data layout subsystem is designed to scale to MLIR's open type and operation system. At the top level, it consists of attribute interfaces that can be implemented by concrete data layout specifications; type interfaces that should be implemented by types subject to data layout; operation interfaces that must be implemented by operations that can serve as data layout scopes (e.g., modules); and dialect interfaces for data layout properties unrelated to specific types. Built-in types are handled specially to decrease the overall query cost. A concrete default implementation of these interfaces is provided in the new Target dialect. Defaults for built-in types that match the current behavior are also provided. Reviewed By: rriddle Differential Revision: https://reviews.llvm.org/D97067
2021-03-11 21:33:44 +08:00
add_subdirectory(Interfaces)
Add build files and update README. * Add initial version of build files; * Update README with instructions to download and build MLIR from github; -- PiperOrigin-RevId: 241102092
2019-03-30 13:10:12 +08:00
add_subdirectory(IR)
add_subdirectory(Pass)
[MLIR] Test pattern benefit sorting between operation specific and operation agnostic patterns. Previously low benefit op-specific patterns never had a chance to match even if high benefit op-agnostic pattern failed to match. This was already fixed upstream, this commit just adds testscase Differential Revision: https://reviews.llvm.org/D98513
2021-03-12 22:39:43 +08:00
add_subdirectory(Rewrite)
[TableGen] Better support for predicate and rewrite rule specification Currently predicates are written with positional placeholders `{N}` and rely on `formatv` as the engine to do substitution. The problem with this approach is that the definitions of those positional placeholders are not consistent; they are entirely up to the defining predicate of question. For example, `{0}` in various attribute constraints is used to mean the attribute, while it is used to main the builder for certain attribute transformations. This can become very confusing. This CL introduces `tgfmt` as a new mechanism to better support for predicate and rewrite rule specification. Instead of entirely relying on positional placeholders, `tgfmt` support both positional and special placeholders. The former is used for DAG operands. The latter, including $_builder, $_op, $_self, are used as special "hooks" to entities in the context. With this, the predicate and rewrite rules specification can be more consistent is more readable. -- PiperOrigin-RevId: 243249671
2019-04-12 20:57:50 +08:00
add_subdirectory(TableGen)
[mlir] Make ConversionTarget dynamic legality callbacks composable * Change callback signature `bool(Operation *)` -> `Optional<bool>(Operation *)` * addDynamicallyLegalOp add callback to the chain * If callback returned empty `Optional` next callback in chain will be called Differential Revision: https://reviews.llvm.org/D110487
2021-07-02 04:41:51 +08:00
add_subdirectory(Transforms)