while folding tensor_reshape op.

While folding reshapes that introduce unit extent dims, the logic to
compute the reassociation maps can be generalized to handle some
corner cases, for example, when the folded shape still has unit-extent
dims but corresponds to folded unit extent dims of the expanded shape.

Differential Revision: https://reviews.llvm.org/D88521

Current setup for conv op vectorization does not enable user to specify tile
sizes as well as dimensions for vectorization. In this commit we change that by
adding tile sizes as pass arguments. Every dimension with corresponding tile
size > 1 is automatically vectorized.

Differential Revision: https://reviews.llvm.org/D88533

This commit adds support for subviews which enable to reduce resulting rank
by dropping static dimensions of size 1.

Differential Revision: https://reviews.llvm.org/D88534

Added support for different function control
in serialization and deserialization.

Reviewed By: mravishankar

Differential Revision: https://reviews.llvm.org/D88280

Start Async dialect for modeling asynchronous execution.

Reviewed By: mehdi_amini, herhut

Differential Revision: https://reviews.llvm.org/D88459

This patch introduces the acc.shutdown operation that represents an OpenACC shutdown directive.
Clauses are derived from the spec 2.14.2

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D88272

This patch introduces the init operation that represents the init executable directive
from the OpenACC 3.0 specifications.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D88254

This patch introduce the wait operation that represent the OpenACC wait directive.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D88125

This patch introduce the update operation that represent the OpenACC update directive.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D88102

Manually-defined named ops do not currently support `init_tensors` or return values and may never support them. Add extra interface to the StructuredOpInterface so that we can still write op-agnostic transformations based on StructuredOpInterface.

This is an NFC extension in preparation for tiling on tensors.

Differential Revision: https://reviews.llvm.org/D88481

This revision changes the signatures of helper function that Linalg uses to create loops so that they can also take iterArgs.
iterArgs are asserted empty to ensure no functional change.
This is a mechanical change in preparation of tiling on linalg on tensors to avoid  polluting the implementation with an NFC change.

Differential Revision: https://reviews.llvm.org/D88480

The previous implementation did not support sinking simple expressions. In particular,
it is often beneficial to sink dim operations.

Differential Revision: https://reviews.llvm.org/D88439

Add a basic verifier for the data operation following the restriction from the standard.

Reviewed By: kiranchandramohan

Differential Revision: https://reviews.llvm.org/D88334

The OmpDialect is in practice optional during translation to LLVM IR: the code is tolerant
to have a "nullptr" when not present / needed.

The dependency still exists on the export to LLVMIR.

Reviewed By: ftynse

Differential Revision: https://reviews.llvm.org/D88351

Adding missing code that should have been part of "D85869: Utility to
vectorize loop nest using strategy."

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D88346

Recently, restrictions on vector reductions were made more relaxed by
accepting any width signless integer and floating-point. This CL relaxes
the restriction even more by including unsigned and signed integers.

Reviewed By: bkramer

Differential Revision: https://reviews.llvm.org/D88442

This patch remove the printer/parser for the acc.data operation since its syntax
fits nicely with the assembly format. It reduces the maintenance for this op.

Reviewed By: kiranchandramohan

Differential Revision: https://reviews.llvm.org/D88330

This patch remove the detach and delete operands. Those operands represent the detach
and delete clauses that will appear in another operation acc.exit_data

Reviewed By: kiranktp, kiranchandramohan

Differential Revision: https://reviews.llvm.org/D88326

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 BlockRange in ODS generated builders as well as other places throughout the code

Differential Revision: https://reviews.llvm.org/D87955

- 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

This prefix is unnecessary as SmallVector is re-exported in the mlir namespace.

Differential Revision: https://reviews.llvm.org/D88025

The assertion falsely expected ranked memrefs only.  Now both, ranked and
unranked memrefs are allowed.

Differential Revision: https://reviews.llvm.org/D88080

This revision allows representing a reduction at the level of linalg on tensors for generic ops by uniformizing with the named ops approach.

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

LLVM can deal with any integer or float type, don't arbitrarily restrict
it to f32/f64/i32/i64.

Differential Revision: https://reviews.llvm.org/D88010

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