The `reifyReturnTypeShapesPerResultDim` method supports shape
inference for rsults that are ranked types. These are used lower in
the codegeneration stack than its counter part `reifyReturnTypeShapes`
which also supports unranked types, and is more suited for use higher
up the compilation stack. To have separation of concerns, this method
is split into its own interface.
See discussion : https://llvm.discourse.group/t/better-layering-for-infershapedtypeopinterface/3823
Differential Revision: https://reviews.llvm.org/D106133
Verify the number of results matches exactly the number of output tensors. Simplify the FillOp verification since part of it got redundant.
Differential Revision: https://reviews.llvm.org/D105427
Remove `getDynOperands` and `createOrFoldDimOp` from MemRef.h to decouple MemRef a bit from Tensor. These two functions are used in other dialects/transforms.
Differential Revision: https://reviews.llvm.org/D105260
* Split memref.dim into two operations: memref.dim and tensor.dim. Both ops have the same builder interface and op argument names, so that they can be used with templates in patterns that apply to both tensors and memrefs (e.g., some patterns in Linalg).
* Add constant materializer to TensorDialect (needed for folding in affine.apply etc.).
* Remove some MemRefDialect dependencies, make some explicit.
Differential Revision: https://reviews.llvm.org/D105165
Adapt the StructuredOp verifier to ensure all operands are either in the input or the output group. The change is possible after adding support for scalar input operands (https://reviews.llvm.org/D104220).
Differential Revision: https://reviews.llvm.org/D104783
Up to now all structured op operands are assumed to be shaped. The patch relaxes this assumption and allows scalar input operands. In contrast to shaped operands scalar operands are not indexed and directly forwarded to the body of the operation. As all other operands, scalar operands are associated to an indexing map that in case of a scalar or a 0D-operand has an empty range.
We will use scalar operands as a replacement for the capture mechanism. In contrast to captures, the approach ensures we can generate the function signature from the operand list and it prevents outdated capture values in case a transformation updates only the capture operand but not the hidden body of a named operation.
Removing captures and updating existing operations such as linalg.fill is left for a later patch.
The patch depends on https://reviews.llvm.org/D103891 and https://reviews.llvm.org/D103890.
Differential Revision: https://reviews.llvm.org/D104109
Adding methods to access operand properties via OpOperands and mark outdated methods as deprecated.
Differential Revision: https://reviews.llvm.org/D103394
The current static checker for linalg does not work on the decreasing
index cases well. So, this is to Update the current static bound checker
for linalg to cover decreasing index cases.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D102302
The patch extends the vectorization pass to lower linalg index operations to vector code. It allocates constant 1d vectors that enumerate the indexes along the iteration dimensions and broadcasts/transposes these 1d vectors to the iteration space.
Differential Revision: https://reviews.llvm.org/D100373
This verification is to check if the indices for static shaped operands
on linalgOps access out of bound memory or not. For dynamic shaped
operands, we would be able to check it on runtime stage.
Found several invalid Linalg ops testcases, and fixed them.
Reviewed By: hanchung
Differential Revision: https://reviews.llvm.org/D98390
A new `InterfaceMethod` is added to `InferShapedTypeOpInterface` that
allows an operation to return the `Value`s for each dim of its
results. It is intended for the case where the `Value` returned for
each dim is computed using the operands and operation attributes. This
interface method is for cases where the result dim of an operation can
be computed independently, and it avoids the need to aggregate all
dims of a result into a single shape value. This also implies that
this is not suitable for cases where the result type is unranked (for
which the existing interface methods is to be used).
Also added is a canonicalization pattern that uses this interface and
resolves the shapes of the output in terms of the shapes of the
inputs. Moving Linalg ops to use this interface, so that many
canonicalization patterns implemented for individual linalg ops to
achieve the same result can be removed in favor of the added
canonicalization pattern.
Differential Revision: https://reviews.llvm.org/D97887
Indexing maps for named ops can reference attributes so that
we can synthesize the indexing map dynamically. This supports
cases like strides for convolution ops. However, it does cause
an issue: now the indexing_maps() function call is dependent
on those attributes.
Linalg ops inherit LinalgOpInterfaceTraits, which calls
verifyStructuredOpInterface() to verify the interface.
verifyStructuredOpInterface() further calls indexing_maps().
Note that trait verification is done before the op itself,
where ODS generates the verification for those attributes.
So we can have indexing_maps() referencing non-existing or
invalid attribute, before the ODS-generated verification
kick in.
There isn't a dependency handling mechansim for traits.
This commit adds new interface methods to query whether an
op hasDynamicIndexingMaps() and then perform
verifyIndexingMapRequiredAttributes() in
verifyStructuredOpInterface() to handle the dependency issue.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D96297
This revision takes advantage of recent extensions to vectorization to refactor contraction detection into a bona fide Linalg interface.
The mlit-linalg-ods-gen parser is extended to support adding such interfaces.
The detection that was originally enabling vectorization is refactored to serve as both a test on a generic LinalgOp as well as to verify ops that declare to conform to that interface.
This is plugged through Linalg transforms and strategies but it quickly becomes evident that the complexity and rigidity of the C++ class based templating does not pay for itself.
Therefore, this revision changes the API for vectorization patterns to get rid of templates as much as possible.
Variadic templates are relegated to the internals of LinalgTransformationFilter as much as possible and away from the user-facing APIs.
It is expected other patterns / transformations will follow the same path and drop as much C++ templating as possible from the class definition.
Differential revision: https://reviews.llvm.org/D95973
This separation improves the layering and paves the way for more interfaces coming up in the future.
Differential revision: https://reviews.llvm.org/D95941
MaheshRavishankar