Convert subtensor and subtensor_insert operations to use their
rank-reduced versions to drop unit dimensions.

Differential Revision: https://reviews.llvm.org/D101495

The current implementation had a bug as it was relying on the target vector
dimension sizes to calculate where to insert broadcast. If several dimensions
have the same size we may insert the broadcast on the wrong dimension. The
correct broadcast cannot be inferred from the type of the source and
destination vector.

Instead when we want to extend transfer ops we calculate an "inverse" map to the
projected permutation and insert broadcast in place of the projected dimensions.

Differential Revision: https://reviews.llvm.org/D101738

Differential Revision: https://reviews.llvm.org/D101771

Add dedicated pass `convert-linalg-tiled-loops-to-scf` to lower
`linalg.tiled_loop`s.

Differential Revision: https://reviews.llvm.org/D101768

* NFC but has some fixes for CMake glitches discovered along the way (things not cleaning properly, co-mingled depends).
* Includes previously unsubmitted fix in D98681 and a TODO to fix it more appropriately in a smaller followup.

Differential Revision: https://reviews.llvm.org/D101493

Differential Revision: https://reviews.llvm.org/D101511

Differential Revision: https://reviews.llvm.org/D101637

Differential Revision: https://reviews.llvm.org/D101643

The converter assumed that all operands have the same type, that's not
true for select.

Differential Revision: https://reviews.llvm.org/D101767

Move TransposeOp lowering in its own populate function as in some cases
it is better to keep it during ContractOp lowering to better
canonicalize it rather than emiting scalar insert/extract.

Differential Revision: https://reviews.llvm.org/D101647

Add missing check in -test-affine-data-copy without which a test case
that has no affine.loads at all would crash this test pass. Fix two
clang-tidy warnings in the file while at this. (Not adding a test case
given the triviality.)

Differential Revision: https://reviews.llvm.org/D101719

* This makes them consistent with custom types/attributes, whose constructors will do a type checked conversion. Of course, the base classes can represent everything so never error.
* More importantly, this makes it possible to subclass Type and Attribute out of tree in sensible ways.

Differential Revision: https://reviews.llvm.org/D101734

Differential Revision: https://reviews.llvm.org/D101747

Differential Revision: https://reviews.llvm.org/D101705

Differential Revision: https://reviews.llvm.org/D101535

1) Canonicalize IndexCast(SExt(x)) => IndexCast(x)
2) Provide constant folds of sign_extend and truncate

Differential Revision: https://reviews.llvm.org/D101714

Differential Revision: https://reviews.llvm.org/D101712

Added canonicalization for vector_load and vector_store. An existing
pattern SimplifyAffineOp can be reused to compose maps that supplies
result into them. Added AffineVectorStoreOp and AffineVectorLoadOp
into static_assert of SimplifyAffineOp to allow operation to use it.

This fixes the bug filed: https://bugs.llvm.org/show_bug.cgi?id=50058

Reviewed By: bondhugula

Differential Revision: https://reviews.llvm.org/D101691

Don't get RegionKindInterface if we won't use it. Noticed by inspection.

(1) migrates the encoding from TensorDialect into the new SparseTensorDialect
(2) replaces dictionary-based storage and builders with struct-like data

Reviewed By: mehdi_amini

Differential Revision: https://reviews.llvm.org/D101669

Stop using the compatibility spellings of `OF_{None,Text,Append}`
left behind by 1f67a3cb. A follow-up
will remove them.

Differential Revision: https://reviews.llvm.org/D101650

Three patterns are added to convert into vector.multi_reduction into a
sequence of vector.reduction as the following:

- Transpose the inputs so inner most dimensions are always reduction.
- Reduce rank of vector.multi_reduction into 2d with inner most
reduction dim (get the 2d canical form)
- 2D canonical form is converted into a sequence of vector.reduction.

There are two things we might worth in a follow up diff:

- An scf.for (maybe optionally) around vector.reduction instead of unrolling it.
- Breakdown the vector.reduction into a sequence of vector.reduction
(e.g tree-based reduction) instead of relying on how downstream dialects
handle it.
  Note: this will requires passing target-vector-length

Differential Revision: https://reviews.llvm.org/D101570

This is the very first step toward removing the glue and clutter from linalg and
replace it with proper sparse tensor types. This revision migrates the LinalgSparseOps
into SparseTensorOps of a sparse tensor dialect. This also provides a new home for
sparse tensor related transformation.

NOTE: the actual replacement with sparse tensor types (and removal of linalg glue/clutter)
will follow but I am trying to keep the amount of changes per revision manageable.

Differential Revision: https://reviews.llvm.org/D101573

Constant-0 dim expr values should be avoided for linalg as it can prevent
fusion. This includes adding support for rank-0 reshapes.

Differential Revision: https://reviews.llvm.org/D101418

This reverts commit a6d92a97.

The build with -DBUILD_SHARED_LIBS=ON is broken.

This was using the untransformed operand, leading to invalid IR.

Differential Revision: https://reviews.llvm.org/D101531

This is the very first step toward removing the glue and clutter from linalg and
replace it with proper sparse tensor types. This revision migrates the LinalgSparseOps
into SparseTensorOps of a sparse tensor dialect. This also provides a new home for
sparse tensor related transformation.

NOTE: the actual replacement with sparse tensor types (and removal of linalg glue/clutter)
will follow but I am trying to keep the amount of changes per revision manageable.

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D101488

This enables to express more complex parallel loops in the affine framework,
for example, in cases of tiling by sizes not dividing loop trip counts perfectly
or inner wavefront parallelism, among others. One can't use affine.max/min
and supply values to the nested loop bounds since the results of such
affine.max/min operations aren't valid symbols. Making them valid symbols
isn't an option since they would introduce selection trees into memref
subscript arithmetic as an unintended and undesired consequence. Also
add support for converting such loops to SCF. Drop some API that isn't used in
the core repo from AffineParallelOp since its semantics becomes ambiguous in
presence of max/min bounds. Loop normalization is currently unavailable for
such loops.

Depends On D101171

Reviewed By: bondhugula

Differential Revision: https://reviews.llvm.org/D101172

Introduce a basic support for parallelizing affine loops with reductions
expressed using iteration arguments. Affine parallelism detector now has a flag
to assume such reductions are parallel. The transformation handles a subset of
parallel reductions that are can be expressed using affine.parallel:
integer/float addition and multiplication. This requires to detect the
reduction operation since affine.parallel only supports a fixed set of
reduction operators.

Reviewed By: chelini, kumasento, bondhugula

Differential Revision: https://reviews.llvm.org/D101171

FillOp allows complex ops, and filling a properly sized buffer with
a default zero complex number is implemented.

Differential Revision: https://reviews.llvm.org/D99939

This will allow the bindings to be built as a library and reused in out-of-tree
projects that want to provide bindings on top of MLIR bindings.

Reviewed By: stellaraccident, mikeurbach

Differential Revision: https://reviews.llvm.org/D101075

Differential Revision: https://reviews.llvm.org/D101456

This revision adds support for vectorizing more general linalg operations with projected permutation maps.

This is achieved by eagerly broadcasting the intermediate vector to the common size
of the iteration domain of the linalg op. This allows a much more natural expression of
generalized vectorization but may introduce additional computations until all the
proper canonicalizations are implemented.

This generalization modifies the vector.transfer_read/write permutation logic and
exposes the fact that the logic employed in vector.contract was too ad-hoc.

As a consequence, changes occur in the permutation / transposition logic for contraction. In turn this prompts supporting more cases in the lowering of contract
to matrix intrinsics, which is required to make the corresponding tests pass.

Differential revision: https://reviews.llvm.org/D101165

The patch extends the OpDSL with support for:
- Constant values
- Capture scalar parameters
- Access the iteration indices using the index operation
- Provide predefined floating point and integer types.

Up to now the patch only supports emitting the new nodes. The C++/yaml path is not fully implemented. The fill_rng_2d operation defined in emit_structured_generic.py makes use of the new DSL constructs.

Differential Revision: https://reviews.llvm.org/D101364

This adds a method to directly invoke `mlirOperationDestroy` on the
MlirOperation wrapped by a PyOperation.

Reviewed By: stellaraccident, mehdi_amini

Differential Revision: https://reviews.llvm.org/D101422

This allows out-of-tree users to derive PyConcreteType to bind custom
types.

The Type version of https://reviews.llvm.org/D101063/new/

Reviewed By: stellaraccident

Differential Revision: https://reviews.llvm.org/D101496