Start of pass to legalize MHLO control flow to SCF for further optimization in common form. The current version just matches a very simple instance (which also happens to occur a few times). Exposes some further canonicalization opportunities that aren't yet addressed.
PiperOrigin-RevId: 329017723
- Use FuncOp::getArguments() and Region::getArguments() and friends where possible
instead of going through the front() block.
PiperOrigin-RevId: 325352975
Create safe or unsafe variants of `shape.broadcast` depending on the context.
The representation by means of an extent tensor is only legal if the operands
are known to be broadcastable. Currently, there is no use in a safe context in
the codebase but it will be used for shape inference eventually.
PiperOrigin-RevId: 325228073
Create safe or unsafe variants of `shape.broadcast` depending on the context.
The representation by means of an extent tensor is only legal if the operands
are known to be broadcastable. Currently, there is no use in a safe context in
the codebase but it will be used for shape inference eventually.
PiperOrigin-RevId: 325079842
The transformation of unranked to ranked operations no longer generates cast
operations for shapes and sizes. Instead, we use the newly introduced support
for extent tensor and index types directly.
PiperOrigin-RevId: 325057440
Create safe or unsafe variants of `shape.broadcast` depending on the context.
The representation by means of an extent tensor is only legal if the operands
are known to be broadcastable. Currently, there is no use in a safe context in
the codebase but it will be used for shape inference eventually.
PiperOrigin-RevId: 325056915
Instead, we invoke multiple test tools in a row in end to end tests now. For hlo dialects and passes, we use mlir-hlo-opt explicitly.
PiperOrigin-RevId: 324989884
Added support for HLO ops bitcast-convert, sort and while in MlirHloBuilder and enabled tests for NonMaxSuppressionV4 and SelfAdjointEigV2Op using these ops.
PiperOrigin-RevId: 324360651
This is required before exporting HLO dialect ops with standard dialect constant to XLA.
Also, sink constants for sort op as well. Added a TODO to generalize this pass to handle more ops and non-const values defined outside.
PiperOrigin-RevId: 324301911
Shuffle files around, use TableGen to register passes, and introduce
a `mlir-hlo-opt.cpp` file to hold the main entry point of the -opt tool
and stop relying on static registration for dialect/passes.
PiperOrigin-RevId: 323674455
This is done through reshaping the unranked tensor into a 1D ranked tensor which will result in a safe broadcast/indexing logic when the other operand is a scalar.
PiperOrigin-RevId: 322553661
Some gathers can be interpreted as torch index selects. Transforming these
cases allow torch_index_select lowerings to be used for certain gathers.
PiperOrigin-RevId: 322255835
The existing conversion no longer worked and was not save to undo. Furthermore, the pattern for mhlo.return had been removed.
Also adds some tests to ensure this does not degrade again.
PiperOrigin-RevId: 321542071
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/40925
…ad of std.store
The xla_lhlo.const lowering uses std.store to store a constant to
0-d memrefs. Update it to affine.store since such an access is trivially
affine (no indices). An affine.store can always be lowered to std.store.
Copybara import of the project:
--
9e18ede72fbbca107177bd742921e4cbf77adc82 by Uday Bondhugula <uday@polymagelabs.com>:
[MLIR] Update lhlo.const to linalg lowering to use affine.store instead of std.store
The xla_lhlo.const lowering uses std.store to store a constant to
0-d memrefs. Update it to affine.store since such an access is trivially
affine (no indices). An affine.store can always be lowered to std.store.
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/40925 from polymage-labs:lhlo_to_linalg_affine_store 9e18ede72fbbca107177bd742921e4cbf77adc82
PiperOrigin-RevId: 320623152
Following on the plan of isolating the compiler/mlir/hlo directory.
Another xla_lhlo dialect will be created under compiler/mlir/xla/ later.
PiperOrigin-RevId: 320210326
Eugene Burmako
A. Unique TensorFlower
Benjamin Kramer
Jacques Pienaar
Mehdi Amini
Hanhan Wang
Robert Suderman
Alexander Belyaev
Rahul Joshi
Stephan Herhut
Smit Hinsu
Thomas Joerg
Tres Popp
Uday Bondhugula