Factor out the functionality into a new function, so that it can be used for creating PadTensorOp tiles.
Differential Revision: https://reviews.llvm.org/D105458
The documentation on these was out of sync with the implementation. Also
the declaration of inputs was repeated when it is already part of the
ArithmeticCastOp definition.
Reviewed By: rriddle
Differential Revision: https://reviews.llvm.org/D105934
Adds zero-preserving unary operators from std. Also adds xor.
Performs minor refactoring to remove "zero" node, and pushed
the irregular logic for negi (not support in std) into one place.
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105928
Previously, linalg bufferization always had to be conservative at function boundaries and assume the most dynamic strided memref layout.
This revision introduce the mechanism to specify a linalg.buffer_layout function argument attribute that carries an affine map used to set a less pessimistic layout.
Reviewed By: ThomasRaoux
Differential Revision: https://reviews.llvm.org/D105859
Integral AND and OR follow the simple conjunction and disjuction rules
for lattice building. This revision also completes some of the Merge
refactoring by moving the remainder parts that are merger specific from
sparsification into utils files.
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105851
Pool operations perform the same shape propagation. Included the shape
propagation and tests for these avg_pool2d and max_pool2d.
Differential Revision: https://reviews.llvm.org/D105665
Right now, we only accept x/c with nonzero c, since this
conceptually can be treated as a x*(1/c) conjunction for both
FP and INT as far as lattice computations go. The codegen
keeps the division though to preserve precise semantics.
See discussion:
https://llvm.discourse.group/t/sparse-tensors-in-mlir/3389/28
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105731
Annotate LinalgNamedStructuredOps.yaml with a comment stating the file is auto-generated and should not be edited manually.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D105809
After the Math 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 Math
dialect operations to LLVM into a separate library and a separate
conversion pass.
Reviewed By: silvas
Differential Revision: https://reviews.llvm.org/D105702
This enables checking the printing flags when formatting names
in SSANameState.
Depends On D105299
Reviewed By: mehdi_amini, bondhugula
Differential Revision: https://reviews.llvm.org/D105300
Use a modeling similar to SCF ParallelOp to support arbitrary parallel
reductions. The two main differences are: (1) reductions are named and declared
beforehand similarly to functions using a special op that provides the neutral
element, the reduction code and optionally the atomic reduction code; (2)
reductions go through memory instead because this is closer to the OpenMP
semantics.
See https://llvm.discourse.group/t/rfc-openmp-reduction-support/3367.
Reviewed By: kiranchandramohan
Differential Revision: https://reviews.llvm.org/D105358
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
For the getters, it is bad practice to keep the reference
around for too long, as explained in the new comment
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105599
This patch adds full qualification to the types and function calls used inside of (Static)InterfaceMethod in OpInterfaces. Without this patch using many of these interfaces in a downstream project yields compiler errors as the types and default implementations are mostly copied verbatim. Without then putting using namespace mlir; in the header file of the implementations of those interfaces, compilation is impossible.
Using fully qualified lookup fixes this issue.
Differential Revision: https://reviews.llvm.org/D105619
This reverts commit 6c0fd4db79.
This simple implementation is unfortunately not extensible and needs to be reverted.
The extensible way should be to extend https://reviews.llvm.org/D104321.
Introduce the exp and log function in OpDSL. Add the soft plus operator to test the emitted IR in Python and C++.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D105420
Remove the GenericOpBase class formerly used to factor out common logic shared be GenericOp and IndexedGenericOp. After removing IndexedGenericOp, the base class is not used anymore.
Differential Revision: https://reviews.llvm.org/D105307
This class and classes that extend it are general utilities for any dialect
that is being converted into the LLVM dialect. They are in no way specific to
Standard-to-LLVM conversion and should not make their users depend on it.
Reviewed By: nicolasvasilache
Differential Revision: https://reviews.llvm.org/D105542
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
"Standard-to-LLVM" conversion is one of the oldest passes in existence. It has
become quite large due to the size of the Standard dialect itself, which is
being split into multiple smaller dialects. Furthermore, several conversion
features are useful for any dialect that is being converted to the LLVM
dialect, which, without this refactoring, creates a dependency from those
conversions to the "standard-to-llvm" one.
Put several of the reusable utilities from this conversion to a separate
library, namely:
- type converter from builtin to LLVM dialect types;
- utility for building and accessing values of LLVM structure type;
- utility for building and accessing values that represent memref in the LLVM
dialect;
- lowering options applicable everywhere.
Additionally, remove the type wrapping/unwrapping notion from the type
converter that is no longer relevant since LLVM types has been reimplemented as
first-class MLIR types.
Reviewed By: pifon2a
Differential Revision: https://reviews.llvm.org/D105534
Fix FlatAffineConstraints::getConstantBoundOnDimSize to ensure that
returned bounds on dim size are always non-negative regardless of the
constraints on that dimension. Add an assertion at the user.
Differential Revision: https://reviews.llvm.org/D105171
This changes the custom syntax of the emitc.include operation for standard includes.
Reviewed By: marbre
Differential Revision: https://reviews.llvm.org/D105281
Different constraints may share the same predicate, in this case, we
will generate duplicate ODS verification function.
Reviewed By: jpienaar
Differential Revision: https://reviews.llvm.org/D104369
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
Basically every kind of parseOptional* method in DialectAsmParser has a corresponding parse* method which will emit an error if the requested token has not been found. An odd one out of this rule is parseOptionalString which does not have a corresponding parseString method.
This patch adds that method and implements it in basically the same fashion as parseKeyword, by first going through parseOptionalString and emitting an error on failure.
Differential Revision: https://reviews.llvm.org/D105406
Same as other CreateLoad-style APIs, these need an explicit type
argument to support opaque pointers.
Differential Revision: https://reviews.llvm.org/D105395
This revision extends the sparse compiler support from fp/int addition and multiplication to fp/int negation and subtraction, thereby increasing the scope of sparse kernels that can be compiled.
Reviewed By: gussmith23
Differential Revision: https://reviews.llvm.org/D105306
Fusion by linearization should not happen when
- The reshape is expanding and it is a consumer
- The reshape is collapsing and is a producer.
The bug introduced in this logic by some recent refactoring resulted
in a crash.
To enforce this (negetive) use case, add a test that reproduces the
error and verifies the fix.
Differential Revision: https://reviews.llvm.org/D104970
Add the min operation to OpDSL and introduce a min pooling operation to test the implementation. The patch is a sibling of the max operation patch https://reviews.llvm.org/D105203 and the min operation is again lowered to a compare and select pair.
Differential Revision: https://reviews.llvm.org/D105345
To make TensorExp clearer, this change refactors the e0/e1 fields into a union: e0/e1 for a binary op tensor expression, and tensor_num for a tensor-kinded tensor expression.
Reviewed By: aartbik
Differential Revision: https://reviews.llvm.org/D105303
Matthias Springer