[mlir] Use value instead of getValue (NFC)

[mlir] Use has_value instead of hasValue (NFC)

[mlir] Update flipped accessors (NFC)

Follow up with memref flipped and flipping any intermediate changes
made.

Revert "Don't use Optional::hasValue (NFC)"

This reverts commit aa8feeefd3ac6c78ee8f67bf033976fc7d68bc6d.

Don't use Optional::hasValue (NFC)

[mlir][sparse] improved testing and codegen for semi-ring operations

The semi-ring blocks were simply "inlined" by the sparse compiler but
without any filtering or patching. This revision improves t

[mlir][sparse] improved testing and codegen for semi-ring operations

The semi-ring blocks were simply "inlined" by the sparse compiler but
without any filtering or patching. This revision improves the analysis
(rejecting blocks that use non-invariant computations from outside
their blocks, except for linalg.index) and also improves the codegen
by properly patching up index computations (previous version crashed).

With a regression test. Also updated the documentation now that the
example code is properly working.

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D128000

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[mlir][sparse_tensor] fix windows build

[mlir][sparse] refactor handling of merger leafs and ops

Using "default:" in the switch statemements that handle all our
merger ops has become a bit cumbersome since it is easy to overlook
parts of

[mlir][sparse] refactor handling of merger leafs and ops

Using "default:" in the switch statemements that handle all our
merger ops has become a bit cumbersome since it is easy to overlook
parts of the code that need to handle ops specifically. By enforcing
full switch statements without "default:", we get a compiler warning
when cases are overlooked.

Reviewed By: wrengr

Differential Revision: https://reviews.llvm.org/D127263

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[mlir][sparse] Add more complex operations.

Support complex operations sqrt, expm1, and tanh.

Add tests.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D126393

[mlir][sparse] Support more complex operations.

Add complex operations abs, neg, sin, log1p, sub and div.

Add test cases.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D126

[mlir][sparse] Support more complex operations.

Add complex operations abs, neg, sin, log1p, sub and div.

Add test cases.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D126027

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[mlir][sparse] Add support for complex.im and complex.re to the sparse compiler.

Add a test.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D125834

[mlir][sparse] introduce complex type to sparse tensor support

This is the first implementation of complex (f64 and f32) support
in the sparse compiler, with complex add/mul as first operations.
Not

[mlir][sparse] introduce complex type to sparse tensor support

This is the first implementation of complex (f64 and f32) support
in the sparse compiler, with complex add/mul as first operations.
Note that various features are still TBD, such as other ops, and
reading in complex values from file. Also, note that the
std::complex<float> had a bit of an ABI issue when passed as
single argument. It is still TBD if better solutions are possible.

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D125596

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[mlir][sparse][NFC] Use RewriterBase/OpBuilder when possible

Most functions do not need a PatternRewriter or ConversionPatternRewriter.

Differential Revision: https://reviews.llvm.org/D125466

Apply clang-tidy fixes for llvm-include-order in Merger.cpp (NFC)

Apply clang-tidy fixes for llvm-else-after-return in Merger.cpp (NFC)

[mlir][sparse] add more zero-preserving unary ops to sparse compiler

Although we now have semi-rings to deal with arbitrary ops,
it is still good to convey zero-preserving semantics of
ops to the sp

[mlir][sparse] add more zero-preserving unary ops to sparse compiler

Although we now have semi-rings to deal with arbitrary ops,
it is still good to convey zero-preserving semantics of
ops to the sparse compiler.

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D125043

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[mlir][sparse] Add lowering for unary and binary ops

Adding lowering for Unary and Binary required several changes due to
their unique nature of containing custom code for different "regions"
of the

[mlir][sparse] Add lowering for unary and binary ops

Adding lowering for Unary and Binary required several changes due to
their unique nature of containing custom code for different "regions"
of the sparse structure being operated on. Along with a Kind, a pointer
to the Operation is passed along to be merged once the lattice
structure is figured out.

The original operation is maintained, as it is required for subsequent
lattice decisions. However, sparse_tensor.binary has some branches
are considered as fully handled and therefore are marked with as
kBinaryBranch to distinguish them.

A unique aspect of the custom code is that sometimes the desired result
is no result at all -- i.e. a user wants overlapping sparse entries to
become empty in the output. The solution to this is to return an
uninitialized Value(), which is checked and handled elsewhere in the
code and results in nothing being written to the output tensor for that
case.

Reviewed By: aartbik

Differential Revision: https://reviews.llvm.org/D123057

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[mlir][NFC] Shift a bunch of dialect includes from the .h to the .cpp

Now that dialect constructors are generated in the .cpp file, we can
drop all of the dependent dialect includes from the .h file

[mlir][NFC] Shift a bunch of dialect includes from the .h to the .cpp

Now that dialect constructors are generated in the .cpp file, we can
drop all of the dependent dialect includes from the .h file.

Differential Revision: https://reviews.llvm.org/D124298

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[mlir][Sparse] Add option for VLA sparsification

Use "enable-vla-vectorization=vla" to generate a vector length agnostic
loops during vectorization. This option works for vectorization strategy 2.

[mlir][Sparse] Add option for VLA sparsification

Use "enable-vla-vectorization=vla" to generate a vector length agnostic
loops during vectorization. This option works for vectorization strategy 2.

Differential Revision: https://reviews.llvm.org/D118379

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[mlir][sparse] index support in sparse compiler codegen

This revision adds support for the linalg.index to the sparse compiler
pipeline. In essence, this adds the ability to refer to indices in
the

[mlir][sparse] index support in sparse compiler codegen

This revision adds support for the linalg.index to the sparse compiler
pipeline. In essence, this adds the ability to refer to indices in
the tensor index expression, as illustrated below:

Y[i, j, k, l, m] = T[i, j, k, l, m] * i * j

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D121251

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[mlir][NFC] Remove a few op builders that simply swap parameter order

Differential Revision: https://reviews.llvm.org/D119093

[mlir][NFC] Add a using for llvm::BitVector to LLVM.h

BitVector is becoming widespread enough that we should add a proper using.

Differential Revision: https://reviews.llvm.org/D118290

Apply clang-tidy fixes for readability-container-size-empty for MLIR (NFC)

Reviewed By: rriddle, Mogball

Differential Revision: https://reviews.llvm.org/D116252

[mlir][sparse] refine simply dynamic sparse tensor outputs

Proper test for sparse tensor outputs is a single condition throughout
the whole tensor index expression (not a general conjunction, since

[mlir][sparse] refine simply dynamic sparse tensor outputs

Proper test for sparse tensor outputs is a single condition throughout
the whole tensor index expression (not a general conjunction, since this
may include other conditions that cause cancellation).

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D114810

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[mlir][sparse] generalize sparse tensor output implementation

Moves sparse tensor output support forward by generalizing from injective
insertions only to include reductions. This revision accepts t

[mlir][sparse] generalize sparse tensor output implementation

Moves sparse tensor output support forward by generalizing from injective
insertions only to include reductions. This revision accepts the case with all
parallel outer and all reduction inner loops, since that can be handled with
an injective insertion still. Next revision will allow the inner parallel loop
to move inward (but that will require "access pattern expansion" aka "workspace").

Reviewed By: bixia

Differential Revision: https://reviews.llvm.org/D114399

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