This PR fixes the warning message due to the non ISO standard usage of
`__FUNCTION__`
```
/home/lewuathe/llvm-project/mlir/test/CAPI/transform_interpreter.c: In function ‘testApplyNamedSequence’:
/home/lewuathe/llvm-project/mlir/test/CAPI/transform_interpreter.c:21:27: warning: ISO C does not support ‘__FUNCTION__’ predefined identifier [-Wpedantic]
21 | fprintf(stderr, "%s\n", __FUNCTION__);
|
```
As `__FUNCTION__` is another name of `__func__` and it conforms to the
specification. We should be able to use `__func__` here.
Ref:
https://stackoverflow.com/questions/52962812/how-to-silence-gcc-pedantic-wpedantic-warning-regarding-function
Compiler
```
Ubuntu clang version 18.1.3 (1)
Target: x86_64-pc-linux-gnu
```
Being able to add custom dialects is one of the big missing pieces of
the C API. This change should make it achievable via IRDL. Hopefully
this should open custom dialect definition to non-C++ users of MLIR.
1. Explicit value means the non-zero value in a sparse tensor. If
explicitVal is set, then all the non-zero values in the tensor have the
same explicit value. The default value Attribute() indicates that it is
not set.
2. Implicit value means the "zero" value in a sparse tensor. If
implicitVal is set, then the "zero" value in the tensor is equal to the
implicit value. For now, we only support `0` as the implicit value but
it could be extended in the future. The default value Attribute()
indicates that the implicit value is `0` (same type as the tensor
element type).
Example:
```
#CSR = #sparse_tensor.encoding<{
map = (d0, d1) -> (d0 : dense, d1 : compressed),
posWidth = 64,
crdWidth = 64,
explicitVal = 1 : i64,
implicitVal = 0 : i64
}>
```
Note: this PR tests that implicitVal could be set to other values as
well. The following PR will add verifier and reject any value that's not
zero for implicitVal.
This patch updates the definition of `omp.wsloop` to enforce the
restrictions of a loop wrapper operation.
Related tests are updated but this PR on its own will not pass premerge
tests. All patches in the stack are needed before it can be compiled and
passes tests.
This commit adds `walk` method to PyOperationBase that uses a python
object as a callback, e.g. `op.walk(callback)`. Currently callback must
return a walk result explicitly.
We(SiFive) have implemented walk method with python in our internal
python tool for a while. However the overhead of python is expensive and
it didn't scale well for large MLIR files. Just replacing walk with this
version reduced the entire execution time of the tool by 30~40% and
there are a few configs that the tool takes several hours to finish so
this commit significantly improves tool performance.
These resulted in link failures:
```
/usr/bin/ld:
tools/mlir/test/CAPI/CMakeFiles/mlir-capi-translation-test.dir/translation.c.o:
in function `main':
translation.c:(.text.main+0x58): undefined reference to
`LLVMContextCreate'
/usr/bin/ld: translation.c:(.text.main+0x9b): undefined reference to
`LLVMDumpModule'
/usr/bin/ld: translation.c:(.text.main+0xa3): undefined reference to
`LLVMDisposeModule'
/usr/bin/ld: translation.c:(.text.main+0xb3): undefined reference to
`LLVMContextDispose'
```
Found in mlir-hs. Not sure why this hasn't been flagged elsewhere.
This commit extends the DIDerivedTypeAttr with the `extraData` field.
For now, the type of it is limited to be a `DINodeAttr`, as extending
the debug metadata handling to support arbitrary metadata nodes does not
seem to be necessary so far.
Following the discussion from [this
thread](https://discourse.llvm.org/t/handling-cyclic-dependencies-in-debug-info/67526/11),
this PR adds support for recursive DITypes.
This PR adds:
1. DIRecursiveTypeAttrInterface: An interface that DITypeAttrs can
implement to indicate that it supports recursion. See full description
in code.
2. Importer & exporter support (The only DITypeAttr that implements the
interface is DICompositeTypeAttr, so the exporter is only implemented
for composites too. There will be two methods that each llvm DI type
that supports mutation needs to implement since there's nothing
general).
---------
Co-authored-by: Tobias Gysi <tobias.gysi@nextsilicon.com>
`%ld` specifier is defined to work on values of type `long`. The parameter given to `fprintf` is of type `intptr_t` whose actual underlying integer type is unspecified. On Unix systems it happens to commonly be `long` but on 64-bit Windows it is defined as `long long`.
The cross-platform way to print a `intptr_t` is to use `PRIdPTR` which expands to the correct format specifier for `intptr_t`. This avoids any undefined behaviour and compiler warnings.
Expose the API for constructing and inspecting StructTypes from the LLVM
dialect. Separate constructor methods are used instead of overloads for
better readability, similarly to IntegerType.
llvm-project/mlir/test/CAPI/sparse_tensor.c:50:43:
error: format specifies type 'unsigned long long' but the argument has type 'MlirSparseTensorLevelType' (aka 'unsigned long') [-Werror,-Wformat]
fprintf(stderr, "level_type: %llu\n", lvlTypes[l]);
~~~~ ^~~~~~~~~~~
%lu
1 error generated.
llvm-project/mlir/test/CAPI/sparse_tensor.c:50:42:
error: format specifies type 'unsigned long' but the argument has type 'MlirSparseTensorLevelType' (aka 'unsigned long long') [-Werror,-Wformat]
50 | fprintf(stderr, "level_type: %lu\n", lvlTypes[l]);
| ~~~ ^~~~~~~~~~~
| %llu
1 error generated.
1. C++ enum is set through enum class LevelType : uint_64.
2. C enum is set through typedef uint_64 level_type. It is due to the
limitations in Windows build: setting enum width to ui64 is not
supported in C.
The "Dim" prefix is a legacy left-over that no longer makes sense, since
we have a very strict "Dimension" vs. "Level" definition for sparse
tensor types and their storage.
The scalable dimension functionality was added to the vector type after
the bindings for it were defined, without the bindings being ever
updated. Fix that.
Enable passing in MlirAsmState optionally (allow for passing in null) to
allow using the more efficient print calling API. The existing print
behavior results in a new AsmState is implicitly created by walking the
parent op and renumbering values. This makes the cost more explicit and
avoidable (by reusing an AsmState).
This commit changes the LLVM dialect's CAPI pointer getters to drop
support for typed pointers. Typed pointers are deprecated and should no
longer be generated.
Fixes https://github.com/llvm/llvm-project/issues/69730 (also see
https://reviews.llvm.org/D155543).
There are two things outstanding (why I didn't land before):
1. add some C API tests for `mlirOperationWalk`;
2. potentially refactor how the invalidation in `run` works; the first
version of the code looked like this:
```cpp
if (invalidateOps) {
auto *context = op.getOperation().getContext().get();
MlirOperationWalkCallback invalidatingCallback =
[](MlirOperation op, void *userData) {
PyMlirContext *context =
static_cast<PyMlirContext *>(userData);
context->setOperationInvalid(op);
};
auto numRegions =
mlirOperationGetNumRegions(op.getOperation().get());
for (int i = 0; i < numRegions; ++i) {
MlirRegion region =
mlirOperationGetRegion(op.getOperation().get(), i);
for (MlirBlock block = mlirRegionGetFirstBlock(region);
!mlirBlockIsNull(block);
block = mlirBlockGetNextInRegion(block))
for (MlirOperation childOp =
mlirBlockGetFirstOperation(block);
!mlirOperationIsNull(childOp);
childOp = mlirOperationGetNextInBlock(childOp))
mlirOperationWalk(childOp, invalidatingCallback, context,
MlirWalkPostOrder);
}
}
```
This is verbose and ugly but it has the important benefit of not
executing `mlirOperationEqual(rootOp->get(), op)` for every op
underneath the root op.
Supposing there's no desire for the slightly more efficient but highly
convoluted approach, I can land this "posthaste".
But, since we have eyes on this now, any suggestions or approaches (or
needs/concerns) are welcome.
Updates:
1. Infer lvlToDim from dimToLvl
2. Add more tests for block sparsity
3. Finish TODOs related to lvlToDim, including adding lvlToDim to python
binding
Verification of lvlToDim that user provides will be implemented in the
next PR.
This is part of the transition toward properly splitting the two groups.
This only introduces new C APIs, the Python bindings are unaffected. No
API is removed.
Note the new surface syntax allows for defining a dimToLvl and lvlToDim
map at once (where usually the latter can be inferred from the former,
but not always). This revision adds storage for the latter, together
with some intial boilerplate. The actual support (inference, validation,
printing, etc.) is still TBD of course.
Enable usage where capturing AsmState is good (e.g., avoiding creating AsmState over and over again when walking IR and printing).
This also only changes one C API to verify plumbing. But using the AsmState makes the cost more explicit than the flags interface (which hides the traversals and construction here) and also enables a more efficient usage C side.
Only construction and type casting are implemented. The method to create
is explicitly named "unsafe" and the documentation calls out what the
caller is responsible for. There really isn't a better way to do this
and retain the power-user feature this represents.
Exposes the existing `get(ShapedType, StringRef, AsmResourceBlob)`
builder publicly (was protected) and adds a CAPI
`mlirUnmanagedDenseBlobResourceElementsAttrGet`.
While such a generic construction interface is a big help when it comes
to interop, it is also necessary for creating resources that don't have
a standard C type (i.e. f16, the f8s, etc).
Previously reviewed/approved as part of https://reviews.llvm.org/D157064
It's recommended practice that people calling MLIR in a loop
pre-create a LLVM ThreadPool and a dialect registry and then
explicitly pass those into a MLIRContext for each compilation.
However, the C API does not expose the functions needed to follow this
recommendation from a project that isn't calling MLIR's C++ dilectly.
Add the necessary APIs to mlir-c, including a wrapper around LLVM's
ThreadPool struct (so as to avoid having to amend or re-export parts
of the LLVM API).
Reviewed By: makslevental
Differential Revision: https://reviews.llvm.org/D153593
Promised interfaces allow for a dialect to "promise" the implementation of an interface, i.e.
declare that it supports an interface, but have the interface defined in an extension in a library
separate from the dialect itself. A promised interface is powerful in that it alerts the user when
the interface is attempted to be used (e.g. via cast/dyn_cast/etc.) and the implementation has
not yet been provided. This makes the system much more robust against misconfiguration,
and ensures that we do not lose the benefit we currently have of defining the interface in
the dialect library.
Differential Revision: https://reviews.llvm.org/D120368
We've observed that the MLIR Jit Engine fails when the `omp` dialect is used due to a failure to register OpenMP-related translations. This small patch addresses this issue.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D151577
This is a major step along the way towards the new STEA design. While a great deal of this patch is simple renaming, there are several significant changes as well. I've done my best to ensure that this patch retains the previous behavior and error-conditions, even though those are at odds with the eventual intended semantics of the `dimToLvl` mapping. Since the majority of the compiler does not yet support non-permutations, I've also added explicit assertions in places that previously had implicitly assumed it was dealing with permutations.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D151505
This is an ongoing series of commits that are reformatting our
Python code.
Reformatting is done with `black`.
If you end up having problems merging this commit because you
have made changes to a python file, the best way to handle that
is to run git checkout --ours <yourfile> and then reformat it
with black.
If you run into any problems, post to discourse about it and
we will try to help.
RFC Thread below:
https://discourse.llvm.org/t/rfc-document-and-standardize-python-code-style
Differential Revision: https://reviews.llvm.org/D150782
This commit is part of the migration of towards the new STEA syntax/design. In particular, this commit includes the following changes:
* Renaming compiler-internal functions/methods:
* `SparseTensorEncodingAttr::{getDimLevelType => getLvlTypes}`
* `Merger::{getDimLevelType => getLvlType}` (for consistency)
* `sparse_tensor::{getDimLevelType => buildLevelType}` (to help reduce confusion vs actual getter methods)
* Renaming external facets to match:
* the STEA parser and printer
* the C and Python bindings
* PyTACO
However, the actual renaming of the `DimLevelType` itself (along with all the "dlt" names) will be handled in a separate commit.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D150330
