This commit adds support to SPIR-V's composite specialization constants.
These are specialization constants which are composed of other spec
constants (whehter scalar or composite), regular constatns, or undef
values.
This commit adds support for parsing, printing, verification, and
(De)serialization.
A few TODOs are still in order:
- Supporting more types of constituents; currently, only scalar spec constatns are supported.
- Extending `spv._reference_of` to support composite spec constatns.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D88568
Add basic canonicalization patterns for the extractMap/insertMap to allow them
to be folded into Transfer ops.
Also mark transferRead as memory read so that it can be removed by dead code.
Differential Revision: https://reviews.llvm.org/D88622
Based on PyAttribute and PyConcreteAttribute classes, this patch implements the bindings of Float Attribute, Integer Attribute and Bool Attribute subclasses.
This patch also defines the `mlirFloatAttrDoubleGetChecked` C API which is bound with the `FloatAttr.get_typed` python method.
Differential Revision: https://reviews.llvm.org/D88531
Previously the actual types were not shown, which makes the message
difficult to grok in the context of long lowering chains. Also, it
appears that there were no actual tests for this.
Differential Revision: https://reviews.llvm.org/D88318
We hit an llvm_unreachable related to unranked memrefs for call ops
with scalar types. Removing the llvm_unreachable since the conversion
should gracefully bail out in the presence of unranked memrefs. Adding
tests to verify that.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88709
Instead of recursive helper method `topologicalSortImpl()`,
sort's implementation is moved to `topologicalSort()` function's
body directly. `llvm::ReversePostOrderTraversal` is used to create
a traversal of blocks in reverse post order.
Reviewed By: kiranchandramohan, rriddle
Differential Revision: https://reviews.llvm.org/D88544
This revision introduces a `subtensor` op, which is the counterpart of `subview` for a tensor operand. This also refactors the relevant pieces to allow reusing the `subview` implementation where appropriate.
This operation will be used to implement tiling for Linalg on tensors.
The documentation for the NormalizeMemRefs pass and the associated MemRefsNormalizable
traits was confusing and not on the website. This update clarifies the language
around the difference between a MemRef Type, an operation that accesses the value of
MemRef Type, and better documents the limitations of the current implementation.
This patch also includes some basic debugging information for the pass so people
might have a chance of figuring out why it doesn't work on their code.
Differential Revision: https://reviews.llvm.org/D88532
```
LinalgTilingOptions &setTileSizes(ValueRange ts)
```
makes it all too easy to create stack-use-after-return errors.
In particular, c694588fc5 introduced one such issue.
Instead just take a copy in the lambda and be done with it.
The current implementation uses a fold expression to add all of the operations at once. This is really nice, but apparently the lifetime of each of the AbstractOperation instances is for the entire expression which may lead to a stack overflow for large numbers of operations. This splits the method in two to allow for the lifetime of the AbstractOperation to be properly scoped.
The pattern is structured similar to other patterns like
LinalgTilingPattern. The fusion patterns takes options that allows you
to fuse with producers of multiple operands at once.
- The pattern fuses only at the level that is known to be legal, i.e
if a reduction loop in the consumer is tiled, then fusion should
happen "before" this loop. Some refactoring of the fusion code is
needed to fuse only where it is legal.
- Since the fusion on buffers uses the LinalgDependenceGraph that is
not mutable in place the fusion pattern keeps the original
operations in the IR, but are tagged with a marker that can be later
used to find the original operations.
This change also fixes an issue with tiling and
distribution/interchange where if the tile size of a loop were 0 it
wasnt account for in these.
Differential Revision: https://reviews.llvm.org/D88435
This is the first of several steps to support distributing large vectors. This
adds instructions extract_map and insert_map that allow us to do incremental
lowering. Right now the transformation only apply to simple pointwise operation
with a vector size matching the multiplicity of the IDs used to distribute the
vector.
This can be used to distribute large vectors to loops or SPMD.
Differential Revision: https://reviews.llvm.org/D88341
Switch to a dummy op in the test dialect so we can remove the -allow-unregistred-dialect
on ops.mlir and invalid.mlir. Change after comment on D88272.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D88587
while folding tensor_reshape op.
While folding reshapes that introduce unit extent dims, the logic to
compute the reassociation maps can be generalized to handle some
corner cases, for example, when the folded shape still has unit-extent
dims but corresponds to folded unit extent dims of the expanded shape.
Differential Revision: https://reviews.llvm.org/D88521
AffineMapAttr is already part of base, it's just impossible to refer to
it from ODS without pulling in the definition from Affine dialect.
Differential Revision: https://reviews.llvm.org/D88555
Current setup for conv op vectorization does not enable user to specify tile
sizes as well as dimensions for vectorization. In this commit we change that by
adding tile sizes as pass arguments. Every dimension with corresponding tile
size > 1 is automatically vectorized.
Differential Revision: https://reviews.llvm.org/D88533
This commit adds support for subviews which enable to reduce resulting rank
by dropping static dimensions of size 1.
Differential Revision: https://reviews.llvm.org/D88534
Added support for different function control
in serialization and deserialization.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D88280
Also add a verifier pass to ExecutionEngine.
It's hard to come up with a test case, since mlir-opt always add location info after parsing it (?)
Differential Revision: https://reviews.llvm.org/D88135
This patch adds support for the 'return' and 'call' ops to the bare-ptr
calling convention. These changes also align the bare-ptr calling
convention code with the latest changes in the default calling convention
and reduce the amount of customization code needed.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87724
* Providing stable, C-accessible definitions for bridging MLIR Python<->C APIs, we eliminate inter-extension dependencies (i.e. they can all share a diamond dependency on the MLIR C-API).
* Just provides accessors for context and module right now.
* Needed in NPComp in ~a week or so for high level Torch APIs.
Differential Revision: https://reviews.llvm.org/D88426
This patch introduces the acc.shutdown operation that represents an OpenACC shutdown directive.
Clauses are derived from the spec 2.14.2
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88272
This patch introduces the init operation that represents the init executable directive
from the OpenACC 3.0 specifications.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88254
This patch introduce the wait operation that represent the OpenACC wait directive.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88125
- Add a minimalist C API for mlir::Dialect.
- Allow one to query the context about registered and loaded dialects.
- Add API for loading dialects.
- Provide functions to register the Standard dialect.
When used naively, this will require to separately register each dialect. When
we have more than one exposed, we can add variadic macros that expand to
individual calls.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D88162
This patch introduce the update operation that represent the OpenACC update directive.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88102
Manually-defined named ops do not currently support `init_tensors` or return values and may never support them. Add extra interface to the StructuredOpInterface so that we can still write op-agnostic transformations based on StructuredOpInterface.
This is an NFC extension in preparation for tiling on tensors.
Differential Revision: https://reviews.llvm.org/D88481
This revision changes the signatures of helper function that Linalg uses to create loops so that they can also take iterArgs.
iterArgs are asserted empty to ensure no functional change.
This is a mechanical change in preparation of tiling on linalg on tensors to avoid polluting the implementation with an NFC change.
Differential Revision: https://reviews.llvm.org/D88480
The previous implementation did not support sinking simple expressions. In particular,
it is often beneficial to sink dim operations.
Differential Revision: https://reviews.llvm.org/D88439
Summary:
========
Bugzilla Ticket No: Bug 46884 [https://bugs.llvm.org/show_bug.cgi?id=46884]
Flush op assembly syntax was ambiguous:
Consider the below test case:
flush operation is not having any arguments.
But the next statement token i.e "%2" is read as the argument for flush operation and then translator issues an error.
***************************************************************
$ cat -n flush.mlir
1 llvm.func @_QQmain(%arg0: !llvm.i32) {
2 %0 = llvm.mlir.constant(1 : i64) : !llvm.i64
3 %1 = llvm.alloca %0 x !llvm.i32 {in_type = i32, name = "a"} : (!llvm.i64) -> !llvm.ptr<i32>
4 omp.flush
5 %2 = llvm.load %1 : !llvm.ptr<i32>
6 llvm.return
7 }
$ mlir-translate -mlir-to-llvmir flush.mlir
flush.mlir:5:6: error: expected ':'
%2 = llvm.load %1 : !llvm.ptr<i32>
^
***************************************************************
Solution:
=========
Introduced begin ( `(` ) and end token ( `)` ) to determince the begin and end of variadic arguments.
The patch includes code changes and testcase modifications.
Reviewed By: Valentin Clement, Mehdi AMINI
Differential Revision: https://reviews.llvm.org/D88376
Add a basic verifier for the data operation following the restriction from the standard.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D88334
The OmpDialect is in practice optional during translation to LLVM IR: the code is tolerant
to have a "nullptr" when not present / needed.
The dependency still exists on the export to LLVMIR.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88351
Adding missing code that should have been part of "D85869: Utility to
vectorize loop nest using strategy."
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D88346
- use select-ops to make the lowering simpler
- change style of FileCheck variables names to be consistent
- change some variable names in the code to be more explicit
Differential Revision: https://reviews.llvm.org/D88258
Recently, restrictions on vector reductions were made more relaxed by
accepting any width signless integer and floating-point. This CL relaxes
the restriction even more by including unsigned and signed integers.
Reviewed By: bkramer
Differential Revision: https://reviews.llvm.org/D88442
(1) simplify integer printing logic by always using 64-bit print
(2) add index support (since vector<16xindex> is planned to be added)
(3) adjust naming convention print_x -> printX
Reviewed By: bkramer
Differential Revision: https://reviews.llvm.org/D88436
ergawy