The patch extends the yaml code generation to support the following new OpDSL constructs:
- captures
- constants
- iteration index accesses
- predefined types
These changes have been introduced by revision
https://reviews.llvm.org/D101364.
Differential Revision: https://reviews.llvm.org/D102075
At present, a lot of code contains main function bodies like "return failed(mlir::MlirOptMain(...);". This is unfortunate for two reasons: a) it uses ADL, which is maybe not what the free "failed" function was designed for; and b) it is a bit awkward to read, requring the reader to both understand the boolean nature of the value and the semantics of main's return value. (And it's also not portable, since 1 is not a portable success value.)
The replacement code, `return mlir::AsMainReturnCode(mlir::MlirOptMain(...))` is a bit more self-explanatory.
The change applies the new function to a few internal uses of MlirOptMain, too.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D102641
test/lib/Transforms/ has bitrot and become somewhat of a dumping grounds for testing pretty much any part of the project. This revision cleans this up, and moves the files within to a directory that reflects what is actually being tested.
Differential Revision: https://reviews.llvm.org/D102456
We are able to bind the result from native function while rewriting
pattern. In matching pattern, if we want to get some values back, we can
do that by passing parameter as return value placeholder. Besides, add
the semantic of '$_self' in NativeCodeCall while matching, it'll be the
operation that defines certain operand.
Differential Revision: https://reviews.llvm.org/D100746
This revision migrates more code from Linalg into the new permanent home of
SparseTensor. It replaces the test passes with proper compiler passes.
NOTE: the actual removal of the last glue and clutter in Linalg will follow
Reviewed By: bixia
Differential Revision: https://reviews.llvm.org/D101811
This commits adds a basic LSP server for MLIR that supports resolving references and definitions. Several components of the setup are simplified to keep the size of this commit down, and will be built out in later commits. A followup commit will add a vscode language client that communicates with this server, paving the way for better IDE experience when interfacing with MLIR files.
The structure of this tool is similar to mlir-opt and mlir-translate, i.e. the implementation is structured as a library that users can call into to implement entry points that contain the dialects/passes that they are interested in.
Note: This commit contains several files, namely those in `mlir-lsp-server/lsp`, that have been copied from the LSP code in clangd and adapted for use in MLIR. This copying was decided as the best initial path forward (discussed offline by several stake holders in MLIR and clangd) given the different needs of our MLIR server, and the one for clangd. If a strong desire/need for unification arises in the future, the existence of these files in mlir-lsp-server can be reconsidered.
Differential Revision: https://reviews.llvm.org/D100439
This matches the current support provided to operations, and allows attaching traits, interfaces, and using the DeclareInterfaceMethods utility. This was missed when attribute/type generation was first added.
Differential Revision: https://reviews.llvm.org/D100233
This is useful for expressing specific table-gen options, like selecting
a particular dialect to print.
Use it to fix the documentation for the `pdl_interp` dialect which is now
generating the first dialect it finds in its input which is `pdl`.
Differential Revision: https://reviews.llvm.org/D100517
We are able to config the reducer pass pipeline through command-line.
Reviewed By: jpienaar, rriddle
Differential Revision: https://reviews.llvm.org/D100155
Add iterator for ReductionNode traversal and use range to indicate the
region we would like to keep. Refactor the interaction between
Pass/Tester/ReductionNode.
Now it'll be easier to add new traversal type and OpReducer
Reviewed By: jpienaar, rriddle
Differential Revision: https://reviews.llvm.org/D99713
This reverts commit a32846b1d0.
The build is broken with -DBUILD_SHARED_LIBS=ON:
tools/mlir/lib/Reducer/CMakeFiles/obj.MLIRReduce.dir/Tester.cpp.o: In function `mlir::Tester::isInteresting(mlir::ModuleOp) const':
Tester.cpp:(.text._ZNK4mlir6Tester13isInterestingENS_8ModuleOpE+0xa8): undefined reference to `mlir::OpPrintingFlags::OpPrintingFlags()'
Tester.cpp:(.text._ZNK4mlir6Tester13isInterestingENS_8ModuleOpE+0xc6): undefined reference to `mlir::Operation::print(llvm::raw_ostream&, mlir::OpPrintingFlags)'
Add iterator for ReductionNode traversal and use range to indicate the region we would like to keep. Refactor the interaction between Pass/Tester/ReductionNode.
Now it'll be easier to add new traversal type and OpReducer
Reviewed By: jpienaar, rriddle
Differential Revision: https://reviews.llvm.org/D99713
These patterns have been used as a prerequisite step for lowering
to SPIR-V. But they don't involve SPIR-V dialect ops; they are
pure memref/vector op transformations. Given now we have a dedicated
MemRef dialect, moving them to Memref/Transforms/, which is a more
suitable place to host them, to allow used by others.
This commit just moves code around and renames patterns/passes
accordingly. CMakeLists.txt for existing MemRef libraries are
also improved along the way.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D100326
Enables performing the same filtering in the op doc definition as in the op definition generator.
Differential Revision: https://reviews.llvm.org/D99793
Right now Elementwise operations fusion in Linalg fuses everything it
can. This can run up against resource limits of the target hardware
without some checks. This patch adds a callback function that clients
can use to implement a cost function. When two elementwise operations
are deemed structurally fusable, the callback can be used to control
if the fusion applies.
Differential Revision: https://reviews.llvm.org/D99820
The issue was introduced in D98468.
The `{0}Regions` is an array of `std::unique_ptr<Region>` objects,
so it should be processed accordingly.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D99332
In particular for Graph Regions, the terminator needs is just a
historical artifact of the generalization of MLIR from CFG region.
Operations like Module don't need a terminator, and before Module
migrated to be an operation with region there wasn't any needed.
To validate the feature, the ModuleOp is migrated to use this trait and
the ModuleTerminator operation is deleted.
This patch is likely to break clients, if you're in this case:
- you may iterate on a ModuleOp with `getBody()->without_terminator()`,
the solution is simple: just remove the ->without_terminator!
- you created a builder with `Builder::atBlockTerminator(module_body)`,
just use `Builder::atBlockEnd(module_body)` instead.
- you were handling ModuleTerminator: it isn't needed anymore.
- for generic code, a `Block::mayNotHaveTerminator()` may be used.
Differential Revision: https://reviews.llvm.org/D98468
Index type is an integer type of target-specific bitwidth present in many MLIR
operations (loops, memory accesses). Converting values of this type to
fixed-size integers has always been problematic. Introduce a data layout entry
to specify the bitwidth of `index` in a given layout scope, defaulting to 64
bits, which is a commonly used assumption, e.g., in constants.
Port builtin-to-LLVM type conversion to use this data layout entry when
converting `index` type and untie it from pointer size. This is particularly
relevant for GPU targets. Keep a possibility to forcibly override the index
type in lowerings.
Depends On D98525
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D98937
This mechanism makes it possible for a dialect to not register all
operations but still answer interface-based queries.
This can useful for dialects that are "open" or connected to an external
system and still interoperate with the compiler. It can also open up the
possibility to have a more extensible compiler at runtime: the compiler
does not need a pre-registration for each operation and the dialect can
inject behavior dynamically.
Reviewed By: rriddle, jpienaar
Differential Revision: https://reviews.llvm.org/D93085
To match an interface or trait, users currently have to use the `MatchAny` tag. This tag can be quite problematic for compile time for things like the canonicalizer, as the `MatchAny` patterns may get applied to *every* operation. This revision adds better support by bucketing interface/trait patterns based on which registered operations have them registered. This means that moving forward we will only attempt to match these patterns to operations that have this interface registered. Two simplify defining patterns that match traits and interfaces, two new utility classes have been added: OpTraitRewritePattern and OpInterfaceRewritePattern.
Differential Revision: https://reviews.llvm.org/D98986
This provides a simplified way to implement 'matchAndRewrite' style
canonicalization patterns for ops that don't need the full power of
RewritePatterns. Using this style, you can implement a static method
with a signature like:
```
LogicalResult AssertOp::canonicalize(AssertOp op, PatternRewriter &rewriter) {
return success();
}
```
instead of dealing with defining RewritePattern subclasses. This also
adopts this for a few canonicalization patterns in the std dialect to
show how it works.
Differential Revision: https://reviews.llvm.org/D99143
The "else" group of an optional element is a collection of elements that get parsed/printed when the anchor of the main element group is *not* present. This is useful when there is a special syntax when an element is not present. The new syntax for an optional element is shown below:
```
optional-group: `(` elements `)` (`:` `(` else-elements `)`)? `?`
```
An example of how this might be used is shown below:
```tablegen
def FooOp : ... {
let arguments = (ins UnitAttr:$foo);
let assemblyFormat = "attr-dict (`foo_is_present` $foo^):(`foo_is_absent`)?";
}
```
would be formatted as such:
```mlir
// When the `foo` attribute is present:
foo.op foo_is_present
// When the `foo` attribute is not present:
foo.op foo_is_absent
```
Differential Revision: https://reviews.llvm.org/D99129
This doesn't change APIs, this just cleans up the many in-tree uses of these
names to use the new preferred names. We'll keep the old names around for a
couple weeks to help transitions.
Differential Revision: https://reviews.llvm.org/D99127
Now that all of the builtin dialect is generated from ODS, its documentation in LangRef can be split out and replaced with references to Dialects/Builtin.md. LangRef is quite crusty right now and should really have a full cleanup done in a followup.
Differential Revision: https://reviews.llvm.org/D98562
This removes the need to construct an APInt for each value, given that it is guaranteed to contain 32 bit elements.
BEGIN_PUBLIC
...text exposed to open source public git repo...
END_PUBLIC
This change combines for ROCm what was done for CUDA in D97463, D98203, D98360, and D98396.
I did not try to compile SerializeToHsaco.cpp or test mlir/test/Integration/GPU/ROCM because I don't have an AMD card. I fixed the things that had obvious bit-rot though.
Reviewed By: whchung
Differential Revision: https://reviews.llvm.org/D98447
Do not limit the number of arguments in rewriter pattern.
Introduce separate `FmtStrVecObject` class to handle
format of variadic `std::string` array.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D97839
This fixes broken JIT functionality on emulator platforms.
With Alex' recent movement towards squashing llvm ir dialects
into target specific dialects, we now must ensure these dialects
are registered to the cpu runner to ensure JIT can lower this
to proper LLVM IR before handing this off to the backend.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D98727
Add a feature to `EnumAttr` definition to generate
specialized Attribute class for the particular enumeration.
This class will inherit `StringAttr` or `IntegerAttr` and
will override `classof` and `getValue` methods.
With this class the enumeration predicate can be checked with simple
RTTI calls (`isa`, `dyn_cast`) and it will return the typed enumeration
directly instead of raw string/integer.
Based on the following discussion:
https://llvm.discourse.group/t/rfc-add-enum-attribute-decorator-class/2252
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D97836
Some parameters to attributes and types rely on special comparison routines other than operator== to ensure equality. This revision adds support for those parameters by allowing them to specify a `comparator` code block that determines if `$_lhs` and `$_rhs` are equal. An example of one of these paramters is APFloat, which requires `bitwiseIsEqual` for bitwise comparison (which we want for attribute equality).
Differential Revision: https://reviews.llvm.org/D98473
The commit in question changed the syntax but did not update the runner
tests. This also required registering the MemRef dialect for custom
parser to work correctly.
Start the description from a new line instead of putting the first
paragraph in the section header. Wrap the class name in backticks to
make it clear that it relates to the code.
Change CUDA integration tests to use mlir-opt + mlir-cpu-runner instead.
Depends On D98203
Reviewed By: herhut
Differential Revision: https://reviews.llvm.org/D98396
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
Clean-up after D98279, remove one call to createConvertGPUKernelToBlobPass().
Depends On D98203
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D98360
Provide default for gpuBinaryAnnotation so that we don't need to specify it in tests.
The annotation likely only needs to be target specific if we want to lower to e.g. both CUDA and ROCDL.
Reviewed By: herhut, bondhugula
Differential Revision: https://reviews.llvm.org/D98168
This allows the caller to distinguish between a parse error or an
unmatched keyword. It fixes the redundant error that was emitted by the
caller when the generated parser would fail.
Differential Revision: https://reviews.llvm.org/D98162
Use `MLIR_LINALG_ODS_GEN` and `MLIR_LINALG_ODS_YAML_GEN` variables
instead of `MLIR_LINALG_ODS_GEN_EXE` and `MLIR_LINALG_ODS_YAML_GEN_EXE`.
The former are defined in PARENT SCOPE only, so the `if` condition
is never evaluates to `TRUE`.
The logic should be the following (taken from tblgen part):
1. `TOOL_NAME` - CACHE variable (default equal to target name).
User can override it to actual executable path.
2. `TOOL_NAME_EXE` - internal variable, initialized to `${TOOL_NAME}` first.
In case of cross-compilation (`LLVM_USE_HOST_TOOLS == TRUE`) if user
didn't set own path to native executable via `TOOL_NAME` variable,
CMake will create separate targets to build native tool and
will override `TOOL_NAME_EXE` to the executable produced by this target.
3. `TOOL_NAME_TARGET` - internal variable, which points to tool target name.
If the native tool is built as described above, it will point to the
target correspondant to that native tool.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D98025
Nicolas Vasilache