Retaining old interface and should be constructable as previous, change would have been NFC except it this doesn't implicitly work with OpAdaptor generated in C++14.
Differential Revision: https://reviews.llvm.org/D106772
Add 'enconding' attribute visitor.
Without it ASM printer doesn't use attribute aliases for 'enconding'.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D105554
Introduce a new rewrite driver (MultiOpPatternRewriteDriver) to rewrite
a supplied list of ops and other ops. Provide a knob to restrict
rewrites strictly to those ops or also to affected ops (but still not to
completely related ops).
This rewrite driver is commonly needed to run any simplification and
cleanup at the end of a transforms pass or transforms utility in a way
that only simplifies relevant IR. This makes it easy to write test cases
while not performing unrelated whole IR simplification that may
invalidate other state at the caller.
The introduced utility provides more freedom to developers of transforms
and transform utilities to perform focussed and local simplification. In
several cases, it provides greater efficiency as well as more
simplification when compared to repeatedly calling
`applyOpPatternsAndFold`; in other cases, it avoids the need to
undesirably call `applyPatternsAndFoldGreedily` to do unrelated
simplification in a FuncOp.
Update a few transformations that were earlier using
applyOpPatternsAndFold (SimplifyAffineStructures,
affineDataCopyGenerate, a linalg transform).
TODO:
- OpPatternRewriteDriver can be removed as it's a special case of
MultiOpPatternRewriteDriver, i.e., both can be merged.
Differential Revision: https://reviews.llvm.org/D106232
We are able to bind NativeCodeCall result as binding operation. To make
table-gen have better understanding in the form of helper function,
we need to specify the number of return values in the NativeCodeCall
template. A VoidNativeCodeCall is added for void case.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D102160
For example, we will generate incorrect code for the pattern,
def : Pat<((FooOp (FooOp, $a, $b), $b)), (...)>;
We didn't allow $b to be bond twice with same operand of same op.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D105677
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
This is the first step to support software pipeline for scf.for loops.
This is only the transformation to create pipelined kernel and
prologue/epilogue.
The scheduling needs to be given by user as many different algorithm
and heuristic could be applied.
This currently doesn't handle loop arguments, this will be added in a
follow up patch.
Differential Revision: https://reviews.llvm.org/D105868
This simplifies the vector to LLVM lowering. Previously, both vector.load/store and vector.transfer_read/write lowered directly to LLVM. With this commit, there is a single path to LLVM vector load/store instructions and vector.transfer_read/write ops must first be lowered to vector.load/store ops.
* Remove vector.transfer_read/write to LLVM lowering.
* Allow non-unit memref strides on all but the most minor dimension for vector.load/store ops.
* Add maxTransferRank option to populateVectorTransferLoweringPatterns.
* vector.transfer_reads with changing element type can no longer be lowered to LLVM. (This functionality is needed only for SPIRV.)
Differential Revision: https://reviews.llvm.org/D106118
This may be necessary in partial multi-stage conversion when a container type
from dialect A containing types from dialect B goes through the conversion
where only dialect A is converted to the LLVM dialect. We will need to keep a
pointer-to-non-LLVM type in the IR until a further conversion can convert
dialect B types to LLVM types.
Reviewed By: wsmoses
Differential Revision: https://reviews.llvm.org/D106076
After the MemRef has been split out of the Standard dialect, the
conversion to the LLVM dialect remained as a huge monolithic pass.
This is undesirable for the same complexity management reasons as having
a huge Standard dialect itself, and is even more confusing given the
existence of a separate dialect. Extract the conversion of the MemRef
dialect operations to LLVM into a separate library and a separate
conversion pass.
Reviewed By: herhut, silvas
Differential Revision: https://reviews.llvm.org/D105625
Simplify vector unrolling pattern to be more aligned with rest of the
patterns and be closer to vector distribution.
The new implementation uses ExtractStridedSlice/InsertStridedSlice
instead of the Tuple ops. After this change the ops based on Tuple don't
have any more used so they can be removed.
This allows removing signifcant amount of dead code and will allow
extending the unrolling code going forward.
Differential Revision: https://reviews.llvm.org/D105381
Refactor the original code to rewrite a PadTensorOp into a
sequence of InitTensorOp, FillOp and InsertSliceOp without
vectorization by default. `GenericPadTensorOpVectorizationPattern`
provides a customized OptimizeCopyFn to vectorize the
copying step.
Reviewed By: silvas, nicolasvasilache, springerm
Differential Revision: https://reviews.llvm.org/D105293
Split out GPU ops library from GPU transforms. This allows libraries to
depend on GPU Ops without needing/building its transforms.
Differential Revision: https://reviews.llvm.org/D105472
Added InferReturnTypeComponents for NAry operations, reshape, and reverse.
With the additional tosa-infer-shapes pass, we can infer/propagate shapes
across a set of TOSA operations. Current version does not modify the
FuncOp type by inserting an unrealized conversion cast prior to any new
non-matchin returns.
Differential Revision: https://reviews.llvm.org/D105312
Add helpers to facilitate adding arguments and results to operations
that implement the `FunctionLike` trait. These operations already have a
convenient argument and result *erasure* mechanism, but a corresopnding
utility for insertion is missing. This introduces such a utility.
* 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
Uses elementwise interface to generalize canonicalization pattern and add a new
pattern for vector.contract case.
Differential Revision: https://reviews.llvm.org/D104343
* Previously, we were only generating .h.inc files. We foresee the need to also generate implementations and this is a step towards that.
* Discussed in https://llvm.discourse.group/t/generating-cpp-inc-files-for-dialects/3732/2
* Deviates from the discussion above by generating a default constructor in the .cpp.inc file (and adding a tablegen bit that disables this in case if this is user provided).
* Generating the destructor started as a way to flush out the missing includes (produces a link error), but it is a strict improvement on its own that is worth doing (i.e. by emitting key methods in the .cpp file, we root vtables in one translation unit, which is a non-controversial improvement).
Differential Revision: https://reviews.llvm.org/D105070
The main goal of this commit is to remove the dependency of Standard dialect on the Tensor dialect.
* Rename SubTensorOp -> tensor.extract_slice, SubTensorInsertOp -> tensor.insert_slice.
* Some helper functions are (already) duplicated between the Tensor dialect and the MemRef dialect. To keep this commit smaller, this will be cleaned up in a separate commit.
* Additional dialect dependencies: Shape --> Tensor, Tensor --> Standard
* Remove dialect dependencies: Standard --> Tensor
* Move canonicalization test cases to correct dialect (Tensor/MemRef).
Note: This is a fixed version of https://reviews.llvm.org/D104499, which was reverted due to a missing update to two CMakeFile.txt.
Differential Revision: https://reviews.llvm.org/D104676
Adapt the FillOp definition to use a scalar operand instead of a capture. This patch is a follow up to https://reviews.llvm.org/D104109. As the input operands are in front of the output operands the patch changes the internal operand order of the FillOp. The pretty printed version of the operation remains unchanged though. The patch also adapts the linalg to standard lowering to ensure the c signature of the FillOp remains unchanged as well.
Differential Revision: https://reviews.llvm.org/D104121
The main goal of this commit is to remove the dependency of Standard dialect on the Tensor dialect.
* Rename ops: SubTensorOp --> ExtractTensorOp, SubTensorInsertOp --> InsertTensorOp
* Some helper functions are (already) duplicated between the Tensor dialect and the MemRef dialect. To keep this commit smaller, this will be cleaned up in a separate commit.
* Additional dialect dependencies: Shape --> Tensor, Tensor --> Standard
* Remove dialect dependencies: Standard --> Tensor
* Move canonicalization test cases to correct dialect (Tensor/MemRef).
Differential Revision: https://reviews.llvm.org/D104499
This revision adds support for passing a functor to SourceMgrDiagnosticHandler for filtering out FileLineColLocs when emitting a diagnostic. More specifically, this can be useful in situations where there may be large CallSiteLocs with locations that aren't necessarily important/useful for users.
For now the filtering support is limited to FileLineColLocs, but conceptually we could allow filtering for all locations types if a need arises in the future.
Differential Revision: https://reviews.llvm.org/D103649
This is similar to attribute and type interfaces and mostly the same mechanism
(FallbackModel / ExternalModel, ODS generation). There are minor differences in
how the concept-based polymorphism is implemented for operations that are
accounted for by ODS backends, and this essentially adds a test and exposes the
API.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D104294
Based on dicussion in
[this](https://llvm.discourse.group/t/remove-canonicalizer-for-memref-dim-via-shapedtypeopinterface/3641)
thread the pattern to resolve the `memref.dim` of a value that is a
result of an operation that implements the
`InferShapedTypeOpInterface` is moved to a separate pass instead of
running it as a canonicalization pass. This allows shape resolution to
happen when explicitly required, instead of automatically through a
canonicalization.
Differential Revision: https://reviews.llvm.org/D104321
This allows for dialects to do different post-processing depending on operations with the inliner (my use case requires different attribute propagation rules depending on call op). This hook runs before the regular processInlinedBlocks method.
Differential Revision: https://reviews.llvm.org/D104399
It may be desirable to provide an interface implementation for an attribute or
a type without modifying the definition of said attribute or type. Notably,
this allows to implement interfaces for attributes and types outside of the
dialect that defines them and, in particular, provide interfaces for built-in
types. Provide the mechanism to do so.
Currently, separable registration requires the attribute or type to have been
registered with the context, i.e. for the dialect containing the attribute or
type to be loaded. This can be relaxed in the future using a mechanism similar
to delayed dialect interface registration.
See https://llvm.discourse.group/t/rfc-separable-attribute-type-interfaces/3637
Depends On D104233
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D104234
This is useful for "build tuple" type ops. In my case, in npcomp, I have
an op:
```
// Result type is `!torch.tuple<!torch.tensor, !torch.tensor>`.
torch.prim.TupleConstruct %0, %1 : !torch.tensor, !torch.tensor
```
and the context is required for the `Torch::TupleType::get` call (for
the case of an empty tuple).
The handling of these FmtContext's in the code is pretty ad-hoc -- I didn't
attempt to rationalize it and just made a targeted fix. As someone
unfamiliar with the code I had a hard time seeing how to more broadly fix
the situation.
Differential Revision: https://reviews.llvm.org/D104274
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
Now that memref supports arbitrary element types, add support for memref of
memref and make sure it is properly converted to the LLVM dialect. The type
support itself avoids adding the interface to the memref type itself similarly
to other built-in types. This allows the shape, and therefore byte size, of the
memref descriptor to remain a lowering aspect that is easier to customize and
evolve as opposed to sanctifying it in the data layout specification for the
memref type itself.
Factor out the code previously in a testing pass to live in a dedicated data
layout analysis and use that analysis in the conversion to compute the
allocation size for memref of memref. Other conversions will be ported
separately.
Depends On D103827
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D103828
Historically, MemRef only supported a restricted list of element types that
were known to be storable in memory. This is unnecessarily restrictive given
the open nature of MLIR's type system. Allow types to opt into being used as
MemRef elements by implementing a type interface. For now, the interface is
merely a declaration with no methods. Later, methods to query, e.g., the type
size or whether a type can alias elements of another type may be added.
Harden the "standard"-to-LLVM conversion against memrefs with non-builtin
types.
See https://llvm.discourse.group/t/rfc-memref-of-custom-types/3558.
Depends On D103826
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D103827
* Rename PadTensorOpVectorizationPattern to GenericPadTensorOpVectorizationPattern.
* Make GenericPadTensorOpVectorizationPattern a private pattern, to be instantiated via populatePadTensorOpVectorizationPatterns.
* Factor out parts of PadTensorOpVectorizationPattern into helper functions.
This commit prepares PadTensorOpVectorizationPattern for a series of subsequent commits that add more specialized PadTensorOp vectorization patterns.
Differential Revision: https://reviews.llvm.org/D103681
Introduces a test pass that rewrites PadTensorOps with static shapes as a sequence of:
```
linalg.init_tensor // to create output
linalg.fill // to initialize with padding value
linalg.generic // to copy the original contents to the padded tensor
```
The pass can be triggered with:
- `--test-linalg-transform-patterns="test-transform-pad-tensor"`
Differential Revision: https://reviews.llvm.org/D102804
Replace the uses of deprecated Structured Op Interface methods in TestLinalgElementwiseFusion.cpp, TestLinalgFusionTransforms.cpp, and Transforms.cpp. The patch is based on https://reviews.llvm.org/D103394.
Differential Revision: https://reviews.llvm.org/D103528
This simplifies various pieces of code that interact with the pass registry, e.g. this removes the need to register passes to get accurate pass pipelines descriptions when generating crash reproducers.
Differential Revision: https://reviews.llvm.org/D101880
This revision allows for attaching "debug labels" to patterns, and provides to FrozenRewritePatternSet for filtering patterns based on these labels (in addition to the debug name of the pattern). This will greatly simplify the ability to write tests targeted towards specific patterns (in cases where many patterns may interact), will also simplify debugging pattern application by observing how application changes when enabling/disabling specific patterns.
To enable better reuse of pattern rewrite options between passes, this revision also adds a new PassUtil.td file to the Rewrite/ library that will allow for passes to easily hook into a common interface for pattern debugging. Two options are used to seed this utility, `disable-patterns` and `enable-patterns`, which are used to enable the filtering behavior indicated above.
Differential Revision: https://reviews.llvm.org/D102441
* A Reducer is a kind of RewritePattern, so it's just the same as
writing graph rewrite.
* ReductionTreePass operates on Operation rather than ModuleOp, so that
* we are able to reduce a nested structure(e.g., module in module) by
* self-nesting.
Reviewed By: jpienaar, rriddle
Differential Revision: https://reviews.llvm.org/D101046
This allows for checking if a given operation may modify/reference/or both a given value. Right now this API is limited to Value based memory locations, but we should expand this to include attribute based values at some point. This is left for future work because the rest of the AliasAnalysis API also has this restriction.
Differential Revision: https://reviews.llvm.org/D101673
* Add `hasCanonicalizer` option to Dialect.
* Initialize canonicalizer with dialect-wide canonicalization patterns.
* Add test case to TestDialect.
Dialect-wide canonicalization patterns are useful if a canonicalization pattern does not conceptually associate with any single operation, i.e., it should not be registered as part of an operation's `getCanonicalizationPatterns` function. E.g., this is the case for canonicalization patterns that match an op interface.
Differential Revision: https://reviews.llvm.org/D103226
