Summary: There was a memory corruption issue where the lifespan of the ArrayRef<StringRef> would fail. Directly passing the data will avoid the issue.
Reviewers: rriddle
Reviewed By: rriddle
Subscribers: mehdi_amini, jpienaar, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, liufengdb, Joonsoo, grosul1, frgossen, Kayjukh, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D78850
Summary: Added support for sparse strings elements. This is a follow up from the original DenseStringElements.
Differential Revision: https://reviews.llvm.org/D78844
Fix affine dialect documentation on valid dimensional values: they also
include affine.parallel IVs.
Differential Revision: https://reviews.llvm.org/D78855
Summary:
* Follows the convention of the tablegen-generated dialects.
* Ensures that vague linkage rules place the definitions in the dialect's object files.
* Allows code that uses RTTI to include MLIR headers (compiled without RTTI) without
type_info link errors.
Reviewers: rriddle
Reviewed By: rriddle
Subscribers: mgorny, mehdi_amini, rriddle, jpienaar, burmako, shauheen, antiagainst, nicolasvasilache, arpith-jacob, mgester, lucyrfox, aartbik, liufengdb, Joonsoo, grosul1, frgossen, llvm-commits
Tags: #llvm
Differential Revision: https://reviews.llvm.org/D78039
- Implement a first constant fold for shape.shape_of (more ops coming in subsequent patches)
- Implement the right builder interfaces for ShapeType and other types
- Splits shape.constant into shape.const_size and shape.const_shape which plays better with dyn_cast and building vs one polymorphic op.
Also, fix the RUN line in ops.mlir to properly verify round-tripping.
The current implementation of this method performs the replacement directly, and thus doesn't support proper back tracking.
Differential Revision: https://reviews.llvm.org/D78790
The elements of a DictionaryAttr are sorted by name. In many situations, e.g NamedAttributeList, we can guarantee that the elements are sorted on construction and remove the need to perform extra checks. In places with lots of calls to attribute methods, this leads to a good performance improvement.
Differential Revision: https://reviews.llvm.org/D78781
Summary:
This is to specify that ParallelOp does not have side effects on its own
but has the effects of all operations executed in its region.
Differential Revision: https://reviews.llvm.org/D78707
This can help provide a common interface for view-like
ops so that for example Linalg's dependency analysis
can avoid relying on concrete ops.
Differential Revision: https://reviews.llvm.org/D78645
Now both Operation::operand_range and Operation::result_range have
.begin() and .end() for ranged-based for loop and we have
ValueRange for wrapping a single Value. We can remove the SmallVector
materialization!
Differential Revision: https://reviews.llvm.org/D78766
Ensure that `gpu.func` is only used within the dedicated `gpu.module`.
Implement the constraint to the GPU dialect and adopt test cases.
Differential Revision: https://reviews.llvm.org/D78541
Summary:
Implemented a DenseStringsElements attr for handling arrays / tensors of strings. This includes the
necessary logic for parsing and printing the attribute from MLIR's text format.
To store the attribute we perform a single allocation that includes all wrapped string data tightly packed.
This means no padding characters and no null terminators (as they could be present in the string). This
buffer includes a first chunk of data that represents an array of StringRefs, that contain address pointers
into the string data, with the length of each string wrapped. At this point there is no Sparse representation
however strings are not typically represented sparsely.
Differential Revision: https://reviews.llvm.org/D78600
This revision removes the multi use-list to ensure that each result gets its own. This decision was made by doing some extensive benchmarking of programs that actually use multiple results. This results in a size increase of 1-word per result >1, but the common case of 1-result remains unaffected. A side benefit is that 0-result operations now shrink by 1-word.
Differential Revision: https://reviews.llvm.org/D78701
it to fusing different kinds of linalg operations on tensors.
The implementation of fusion on tensor was initially planned for just
GenericOps (and maybe IndexedGenericOps). With addition of
linalg.tensor_reshape, and potentially other such non-structured ops,
refactor the existing implementation to allow easier specification of
fusion between different linalg operations on tensors.
Differential Revision: https://reviews.llvm.org/D78463
367229e100 retired ValueHandle but
mistakenly removed the implementation for `negate` which was not
tested and would result in linking errors.
This revision adds the implementation back and provides a test.
The current Liveness analysis does not support operations with nested regions.
This causes issues when querying liveness information about blocks nested within
operations. Furthermore, the live-in and live-out sets are not computed properly
in these cases.
Differential Revision: https://reviews.llvm.org/D77714
It currently requires that the condition match the shape of the selected value, but this is only really useful for things like masks. This revision allows for the use of i1 to mean that all of the vector/tensor is selected. This also matches the behavior of LLVM select. A benefit of this change is that transformations that want to generate selects, like those on the CFG, don't have to special case vector/tensor. Previously the only way to generate a select from an i1 was to use a splat, but that doesn't support dynamically shaped/unranked tensors.
Differential Revision: https://reviews.llvm.org/D78690
This revision adds support for canonicalizing the following:
```
br ^bb1
^bb1
br ^bbN(...)
br ^bbN(...)
```
Differential Revision: https://reviews.llvm.org/D78683
This revision adds support for canonicalizing the following:
```
cond_br %cond, ^bb1(A, ..., N), ^bb1(A, ..., N)
br ^bb1(A, ..., N)
```
If the operands to the successor are different and the cond_br is the only predecessor, we emit selects for the branch operands.
```
cond_br %cond, ^bb1(A), ^bb1(B)
%select = select %cond, A, B
br ^bb1(%select)
```
Differential Revision: https://reviews.llvm.org/D78682
Summary:
This test is in a different file because it contains a literal NUL
character, which causes various tools to treat it as a binary file.
Hence it is useful to have this test kept in a separate, rarely-changing
file.
Differential Revision: https://reviews.llvm.org/D78689
Summary:
Use a nested symbol to identify the kernel to be invoked by a `LaunchFuncOp` in the GPU dialect.
This replaces the two attributes that were used to identify the kernel module and the kernel within seperately.
Differential Revision: https://reviews.llvm.org/D78551
Summary:
Use the shortcu `kernel` for the `gpu.kernel` attribute of `gpu.func`.
The parser supports this and test cases are easier to read.
Differential Revision: https://reviews.llvm.org/D78542
Summary:
Fix a broken test case in the `invalid.mlir` lit test case.
`expect` was missing its `e`.
Differential Revision: https://reviews.llvm.org/D78540
We also need to lock the LLVMDialect mutex when initializing
LLVM targets or destroying llvm modules concurrently. Added another
scoped lock to that effect.
Differential Revision: https://reviews.llvm.org/D78580
The buffer allocated by a promotion can be subject to other transformations afterward. For example it could be vectorized, in which case it is needed to ensure that this buffer is memory-aligned.
Differential Revision: https://reviews.llvm.org/D78556
This revision is the first in a set of improvements that aim at allowing
more generalized named Linalg op generation from a mathematical
specification.
This revision allows creating a new op and checks that the parser,
printer and verifier are hooked up properly.
This opened up a few design points that will be addressed in the future:
1. A named linalg op has a static region builder instead of an
explicitly parsed region. This is not currently compatible with
assemblyFormat so a custom parser / printer are needed.
2. The convention for structured ops and tensor return values needs to
evolve to allow tensor-land and buffer land specifications to agree
3. ReferenceIndexingMaps and referenceIterators will need to become
static to allow building attributes at parse time.
4. Error messages will be improved once we have 3. and we pretty print
in custom form.
Differential Revision: https://reviews.llvm.org/D78327
Benjamin Kramer