[mlir] Enable decoupling two kinds of greedy behavior. (#104649)

The greedy rewriter is used in many different flows and it has a lot of
convenience (work list management, debugging actions, tracin

[mlir] Enable decoupling two kinds of greedy behavior. (#104649)

The greedy rewriter is used in many different flows and it has a lot of
convenience (work list management, debugging actions, tracing, etc). But
it combines two kinds of greedy behavior 1) how ops are matched, 2)
folding wherever it can.

These are independent forms of greedy and leads to inefficiency. E.g.,
cases where one need to create different phases in lowering and is
required to applying patterns in specific order split across different
passes. Using the driver one ends up needlessly retrying folding/having
multiple rounds of folding attempts, where one final run would have
sufficed.

Of course folks can locally avoid this behavior by just building their
own, but this is also a common requested feature that folks keep on
working around locally in suboptimal ways.

For downstream users, there should be no behavioral change. Updating
from the deprecated should just be a find and replace (e.g., `find ./
-type f -exec sed -i
's|applyPatternsAndFoldGreedily|applyPatternsGreedily|g' {} \;` variety)
as the API arguments hasn't changed between the two.

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[mlir][linalg] unfold projected permutation. (#114704)

Patterns to decompose the input operand(s) of a linalg.generic that has
a projected permutation` affine-map -- i.e. effectively a folded `tra

[mlir][linalg] unfold projected permutation. (#114704)

Patterns to decompose the input operand(s) of a linalg.generic that has
a projected permutation` affine-map -- i.e. effectively a folded `transpose`,
`broadcast`, or a mixture of two -- into explicit transpose and broadcast.
This is useful for instance when trying to recognize named ops.
email: quic_mabsar@quicinc.com

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[mlir][linalg] raise generic to named ops. (#110421)

Add support for specializing linalg.broadcast and linalg.transform from generic. Also, does some refactoring to reuse specialization checks, migr

[mlir][linalg] raise generic to named ops. (#110421)

Add support for specializing linalg.broadcast and linalg.transform from generic. Also, does some refactoring to reuse specialization checks, migrating some common uses to op interface methods.

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[mlir] Use llvm::is_contained (NFC) (#102714)

[MLIR][Linalg] Add pass to convert linalg.generic back to named ops (#95656)

Add a new mlir-opt pass `--linalg-specialize-generic-ops` which lifts generic,
where possible, to linalg named ops.
Mu

[MLIR][Linalg] Add pass to convert linalg.generic back to named ops (#95656)

Add a new mlir-opt pass `--linalg-specialize-generic-ops` which lifts generic,
where possible, to linalg named ops.
Much like `-linalg-generalize-named-ops` lowers named ops to linalg.generic .
Also add patterns to recognize contractions which can be specialized from
linalg.generic to named op: `linalg.{batch_}?matmul{_transpose_(a|b)}?`

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[MLIR][Linalg] Add more specialize patterns (#91153)

Currently only linalg.copy is recognized when trying to specialize
linalg.generics back to named op. This diff enables recognition of more
gene

[MLIR][Linalg] Add more specialize patterns (#91153)

Currently only linalg.copy is recognized when trying to specialize
linalg.generics back to named op. This diff enables recognition of more
generic to named op e.g. linalg.fill, elemwise unary/binary.

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[MLIR][Linalg] Introduce SpecializeOp (#70326)

Introduce an operation to specialize linalg.generics, for example,
detecting a linalg.generic that is semantically equivalent to a
linalg.copy and re

[MLIR][Linalg] Introduce SpecializeOp (#70326)

Introduce an operation to specialize linalg.generics, for example,
detecting a linalg.generic that is semantically equivalent to a
linalg.copy and replacing the former with the latter. After code
generation, it is helpful to lower named operations to vendor-optimized
libraries.

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