[mlir] fold more eagerly in structured op splitting

Existing implementation of structured op splitting creates several
affine.apply and affine.min operations in its subshape computation.
As these sh

[mlir] fold more eagerly in structured op splitting

Existing implementation of structured op splitting creates several
affine.apply and affine.min operations in its subshape computation.
As these shapes are further used in data slice extraction, this may lead
to slice shapes being dynamic even when the original shapes and the
splitting point are static. This is particularly visible when splitting
is combined with further subsetting transformations such as tiling. Use
composition and folding more aggressively in splitting to avoid this.

In particular, introduce a `createComposedAffineMin` function that the
affine map used in "min" with the maps used by any `affine.apply` that
may be feeding the operands to the "min". This enables production of
more static shapes. Also introduce a `createComposedFoldedAffineApply`
function that combines the existing `createComposedAffineApply` with
in-place folding to propagate constants produced by zero-input affine
maps. Using these when splitting allows the subsequent canonicalizer
pass to recover static shapes for structured ops.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D129379

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[mlir] Handle linalg.index correctly in TilingInterface

The existing implementation of the TilingInterface for Linalg ops was not
modifying the `linalg.index` ops contained within other Linalg ops (

[mlir] Handle linalg.index correctly in TilingInterface

The existing implementation of the TilingInterface for Linalg ops was not
modifying the `linalg.index` ops contained within other Linalg ops (they need
to be summed up with the values of respective tile loop induction variables),
which led to the interface-based tiling being incorrect for any Linalg op with
index semantics.

In the process, fix the function performing the index offsetting to use the
pattern rewriter API instead of RAUW as it is being called from patterns and
may mess up the internal state of the rewriter. Also rename the function to
clearly catch all uses.

Depends On D129365

Reviewed By: mravishankar

Differential Revision: https://reviews.llvm.org/D129366

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[mlir] Allow Tile transform op to take dynamic sizes

Extend the definition of the Tile structured transform op to enable it
accepting handles to operations that produce tile sizes at runtime. This i

[mlir] Allow Tile transform op to take dynamic sizes

Extend the definition of the Tile structured transform op to enable it
accepting handles to operations that produce tile sizes at runtime. This is
useful by itself and prepares for more advanced tiling strategies. Note that
the changes are relevant only to the transform dialect, the tiling
transformation itself already supports dynamic sizes.

Depends On D129216

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D129217

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[mlir] Structured transforms: introduce op splitting

Introduce a new transformation on structured ops that splits the iteration
space into two parts along the specified dimension. The index at which

[mlir] Structured transforms: introduce op splitting

Introduce a new transformation on structured ops that splits the iteration
space into two parts along the specified dimension. The index at which the
splitting happens may be static or dynamic. This transformation can be seen as
a rudimentary form of index-set splitting that only supports the splitting
along hyperplanes parallel to the iteration space hyperplanes, and is therefore
decomposable into per-dimension application.

It is a key low-level transformation that enables independent scheduling for
different parts of the iteration space of the same op, which hasn't been
possible previously. It may be used to implement, e.g., multi-sized tiling. In
future, peeling can be implemented as a combination of split-off amount
computation and splitting.

The transformation is conceptually close to tiling in its separation of the
iteration and data spaces, but cannot be currently implemented on top of
TilingInterface as the latter does not properly support `linalg.index`
offsetting.

Note that the transformation intentionally bypasses folding of
`tensor.extract_slice` operations when creating them as this folding was found
to prevent repeated splitting of the same operation because due to internal
assumptions about extract/insert_slice combination in dialect utilities.

Reviewed By: nicolasvasilache

Differential Revision: https://reviews.llvm.org/D129090

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