Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/43069
The legalization of mlhlo.ReturnOp to lhlo.TerminatorOp by using BufferAssignmentReturnOpConverter fails since the Memref typed results (or the Memref typed operands of Return operation) are set to stay as results after legalization but lhlo.TerminatorOp doesn't accept any operands. Therefore, BufferAssignmentReturnOpConverter must be replaced with a manual conversion that removes all operands of mlhlo.ReturnOp and inserts copy operations in their places.
Copybara import of the project:
--
8be0435b0147263c3872bedec58fd215f784b450 by Ehsan Toosi <ehsan.nadjaran_toosi@dfki.de>:
[hlo] Unbreak hlo-legalize-to-lhlo test
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/43069 from dfki-ehna:fix_hlo_legalize_to_lhlo_test 8be0435b0147263c3872bedec58fd215f784b450
PiperOrigin-RevId: 330907602
* Unified TF->Cubin and TF->Kernel_with_host side lowering in `kernel_creator.h|cc`
* Added a pass that attaches GPU binary blob to GPUModuleOp
* Refactored most of the code.
* Added tf_to_kernel binary that emits obj file
PiperOrigin-RevId: 330494488
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
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/42509
Add folder for mhlo GetDimensionSizeOp (`mhlo.get_dimension_size`).
`get_dimension_size` folds to a constant when the corresponding tensor
dimension size is statically known / constant.
Copybara import of the project:
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5994915525ec2e932125aa1f133ce2260ba100af by Uday Bondhugula <uday@polymagelabs.com>:
[MLIR] Add folder for mhlo get_dimension_size
Add folder for mhlo GetDimensionSizeOp. get_dimension_size folds to a
constant when the corresponding tensor dimension size is statically
known / constant.
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/42509 from polymage-labs:get_dimension_size_fold 5994915525ec2e932125aa1f133ce2260ba100af
PiperOrigin-RevId: 328222517
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/42508
An lmhlo.constant op on an memref that is locally allocated and with
no users other than dealloc's can be deleted. Add a canonicalization
pattern for this.
Copybara import of the project:
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8758c409a15f567e7cb8e1077faa020f5705c85a by Uday Bondhugula <uday@polymagelabs.com>:
[MLIR] Erase dead lmhlo.constant ops
An lmhlo.constant op on an memref that is locally allocated and with
no other users (other than dealloc's) can be deleted. Add a
canonicalization patter for this.
COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/42508 from polymage-labs:lhlo_constant_erase 8758c409a15f567e7cb8e1077faa020f5705c85a
PiperOrigin-RevId: 328042416
By adding support for complex types to GetScalarOfType and using appropriate
choice of limits for initial values in the unsorted segment reduction ops.
PiperOrigin-RevId: 327061577
This allows specifying a constant whose shape is only known when operand shape is. Also use it to update tf.Acos legalization.
PiperOrigin-RevId: 325860604
HLO requires that the element types match for all start index parameters. Right now we don't catch this invalid case until export, so adding a check in the verifier so that we catch this sooner.
This also requires a small tweak to the TF InplaceUpdate op lowering.
PiperOrigin-RevId: 325463796
- Use FuncOp::getArguments() and Region::getArguments() and friends where possible
instead of going through the front() block.
PiperOrigin-RevId: 325352975
For input and output dimensions which must match, we shouldn't fail in the case where one dim is dynamic and the other is static. This is insufficient information to conclude a dimension mismatch.
PiperOrigin-RevId: 325344738
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
The computation of a broadcasted shape forced the use of the shape type unnecessarily, which blocked further canonicalizations.
PiperOrigin-RevId: 323783998
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
A. Unique TensorFlower
Ehsan Toosi
Robert Suderman
Mehdi Amini
Alexander Belyaev
Eugene Burmako
Benjamin Kramer
Jacques Pienaar
Uday Bondhugula
Hanhan Wang
Richard Uhler
Andy Ly
Lucy Fox
Rahul Joshi
Stephan Herhut
Smit Hinsu
Thomas Joerg
Tres Popp