Fixed an error when deserializing the SPIR-V binary
to MLIR SPIR-V. Before, the SPIR-V dialect was not loaded
explicitly into the context, which resulted in unregistered
operation error.
Reviewed By: antiagainst
Differential Revision: https://reviews.llvm.org/D88223
- Use TypeRange instead of ArrayRef<Type> where possible.
- Change some of the custom builders to also use TypeRange
Differential Revision: https://reviews.llvm.org/D87944
This patch switch from using bool variables to OptionalParseResult for the parsing
inside loop operation. This is already done for parallel operation and this patch unify this
in the dialect.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D88111
A sequence of two reshapes such that one of them is just adding unit
extent dims can be folded to a single reshape.
Differential Revision: https://reviews.llvm.org/D88057
The assertion falsely expected ranked memrefs only. Now both, ranked and
unranked memrefs are allowed.
Differential Revision: https://reviews.llvm.org/D88080
This patch adds a utility based on SuperVectorizer to vectorize an
affine loop nest using a given vectorization strategy. This strategy allows
targeting specific loops for vectorization instead of relying of the
SuperVectorizer analysis to choose the right loops to vectorize.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D85869
This adds support for the interface and provides unambigious information
on the control flow as it is unconditional on any runtime values.
The code is tested through confirming that buffer-placement behaves as
expected.
Differential Revision: https://reviews.llvm.org/D87894
Vendor/device information are not resource limits. Moving to
target environment directly for better organization.
Reviewed By: mravishankar
Differential Revision: https://reviews.llvm.org/D87911
Roundtripping SPIR-V modules used the same MLIRContext object for both
ways of the trip. This resulted in deserialization using a context
object already containing Types constructed during serialization.
This commit rectifies that by creating a new MLIRContext during
deserialization.
Reviewed By: mravishankar, antiagainst
Differential Revision: https://reviews.llvm.org/D87692
Add missing operands to represent copyin with readonly modifier, copyout with zero modifier
and create with zero modifier.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87874
Following patch D87712, this patch switch AnyInteger for operands gangNum, gangStatic,
workerNum, vectoreLength and tileOperands to Index and AnyInteger.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87848
This revision allows representing a reduction at the level of linalg on tensors for named ops. When a structured op has a reduction and returns tensor(s), new conventions are added and documented.
As an illustration, the syntax for a `linalg.matmul` writing into a buffer is:
```
linalg.matmul ins(%a, %b : memref<?x?xf32>, tensor<?x?xf32>)
outs(%c : memref<?x?xf32>)
```
, whereas the syntax for a `linalg.matmul` returning a new tensor is:
```
%d = linalg.matmul ins(%a, %b : tensor<?x?xf32>, memref<?x?xf32>)
init(%c : memref<?x?xf32>)
-> tensor<?x?xf32>
```
Other parts of linalg will be extended accordingly to allow mixed buffer/tensor semantics in the presence of reductions.
This op is a catch-all for creating witnesses from various random kinds
of constraints. In particular, I when dealing with extents directly,
which are of `index` type, one can directly use std ops for calculating
the predicates, and then use cstr_require for the final conversion to a
witness.
Differential Revision: https://reviews.llvm.org/D87871
Add support to tile affine.for ops with parametric sizes (i.e., SSA
values). Currently supports hyper-rectangular loop nests with constant
lower bounds only. Move methods
- moveLoopBody(*)
- getTileableBands(*)
- checkTilingLegality(*)
- tilePerfectlyNested(*)
- constructTiledIndexSetHyperRect(*)
to allow reuse with constant tile size API. Add a test pass -test-affine
-parametric-tile to test parametric tiling.
Differential Revision: https://reviews.llvm.org/D87353
Add support for return values in affine.for yield along the same lines
as scf.for and affine.parallel.
Signed-off-by: Abhishek Varma <abhishek.varma@polymagelabs.com>
Differential Revision: https://reviews.llvm.org/D87437
Fold the operation if the source is a scalar constant or splat constant.
Update transform-patterns-matmul-to-vector.mlir because the broadcast ops are folded in the conversion.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D87703
This patch change the type of operands async, wait, numGangs, numWorkers and vectorLength from index
to AnyInteger to fit with acc.loop and the OpenACC specification.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87712
Adds a pattern that replaces a chain of two tensor_cast operations by a single tensor_cast operation if doing so will not remove constraints on the shapes.
ConvOp vectorization supports now only convolutions of static shapes with dimensions
of size either 3(vectorized) or 1(not) as underlying vectors have to be of static
shape as well. In this commit we add support for convolutions of any size as well as
dynamic shapes by leveraging existing matmul infrastructure for tiling of both input
and kernel to sizes accepted by the previous version of ConvOp vectorization.
In the future this pass can be extended to take "tiling mask" as a user input which
will enable vectorization of user specified dimensions.
Differential Revision: https://reviews.llvm.org/D87676
These canonicalizations are already handled by folding which will occur
in a superset of situations, so they are being removed.
Differential Revision: https://reviews.llvm.org/D87706
Add missing operands to represent copin with readonly modifier, copyout with zero
modifier, create with zero modifier and default clause.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87733
Rename 'setInsertionPointAfter(Value)' API to avoid ambiguity with
'setInsertionPointAfter(Operation *)' for SingleResult operations which
implicitly convert to Value (see D86756).
Differential Revision: https://reviews.llvm.org/D87155
Add a verifier for the loop op in the OpenACC dialect. Check basic restriction
from 2.9 Loop construct from the OpenACC 3.0 specs.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87546
This patch adds the missing print for the vector_length in the parallel operation.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87630
This add canonicalizer for
- extracting an element from a dynamic_tensor_from_elements
- propagating constant operands to the type of dynamic_tensor_from_elements
Differential Revision: https://reviews.llvm.org/D87525
Now backends spell out which namespace they want to be in, instead of relying on
clients #including them inside already-opened namespaces. This also means that
cppNamespaces should be fully qualified, and there's no implicit "::mlir::"
prepended to them anymore.
Reviewed By: mehdi_amini
Differential Revision: https://reviews.llvm.org/D86811
Added support to the Std dialect cast operations to do casts in vector types when feasible.
Reviewed By: ftynse
Differential Revision: https://reviews.llvm.org/D87410
This introduces a builder for the more general case that supports zero
elements (where the element type can't be inferred from the ValueRange,
since it might be empty).
Also, fix up some cases in ShapeToStandard lowering that hit this. It
happens very easily when dealing with shapes of 0-D tensors.
The SameOperandsAndResultElementType is redundant with the new
TypesMatchWith and prevented having zero elements.
Differential Revision: https://reviews.llvm.org/D87492
Addressed some CR issues pointed out in D87111. Formatting and other nits.
The original Diff D87111 - Add an option for unrolling loops up to a factor.
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D87313
This revision refactors and cleans up a bunch of things to simplify StructuredOpInterface
before work can proceed on Linalg on tensors:
- break out pieces of the StructuredOps trait that are part of the StructuredOpInterface,
- drop referenceIterators and referenceIndexingMaps that end up being more confusing than useful,
- drop NamedStructuredOpTrait
Previously only the input type was printed, and the parser applied it to
both input and output, creating an invalid transpose. Print and parse
both types, and verify that they match.
Differential Revision: https://reviews.llvm.org/D87462
The LinalgTilingPattern class dervied from the base deletes the
original operation. This allows for the use case where the more
transformations are necessary on the original operation after
tiling. In such cases the pattern can derive from
LinalgBaseTilingPattern instead of LinalgTilingPattern.
Differential Revision: https://reviews.llvm.org/D87308
This patch adds a new named structured op to accompany linalg.matmul and
linalg.matvec. We needed it for our codegen, so I figured it would be useful
to add it to Linalg.
Reviewed By: nicolasvasilache, mravishankar
Differential Revision: https://reviews.llvm.org/D87292
Also refactor the getViewSizes method to work on LinalgOp instead of
being a templated version. Keeping the templated version for
compatibility.
Differential Revision: https://reviews.llvm.org/D87303
Take advantage of the new `dynamic_tensor_from_elements` operation in `std`.
Instead of stack-allocated memory, we can now lower directly to a single `std`
operation.
Differential Revision: https://reviews.llvm.org/D86935
Currently, there is no option to allow for unrolling a loop up to a specific factor (specified by the user).
The code for doing that is there and there are benefits when unrolling is done to smaller loops (smaller than the factor specified).
Reviewed By: bondhugula
Differential Revision: https://reviews.llvm.org/D87111
