This just adds support for it in the op, but keeps the production/uses as is (e.g., single tensor or tuple) matching what XLA export requires. In follow up here, would be to add pass for export to retuple and then the canonical form could be changed. Tuple'ing given control flow via regions & multi-result operations does not add representational power and all the get_tuple_element ops obscure the computation.
The old form allowed single tensor or tuple. The new variadic number of tensor or tuples as tuples may be nested, so the input could have (Tensor<..>, Tuple<Tensor<...>, Tuple<...>, ...>, Tensor<...>) and HLO_Tensor doesn't allow Tuples.
PiperOrigin-RevId: 378934388
Adds import/export/verifier support as well.
Also makes `channel_handle` uniform across mhlo.all_reduce and mhlo.all-gather.
PiperOrigin-RevId: 377323468
This matches the behavior of mhlo.case. Additionally, fix the verification of CaseOp in the case of nested ops with mhlo.return-containing regions.
PiperOrigin-RevId: 365936672
Make the error message a bit more verbose & it is cheaper to verify the elements rather than creating a (potentially) new type.
PiperOrigin-RevId: 363073909
Previously this would be too strict and fail if dynamic and static dims were
compared. Dynamic/unknown are treated as "maybe equal" to a static value without further info, so at this layer don't flag as invalid unless truly are.
PiperOrigin-RevId: 360189086
Verification of HLO_BroadcastInDimOp was previously failing or crashing if the
operand had a dynamic shape or was unranked. Update the verification code to
allow the operand to be unranked or have dynamic shape.
PiperOrigin-RevId: 358056793
- Also fixed kernel_gen embed_memref_prints to mark the declarations inserted private.
- This is in prep for proposed MLIR change to disallow public declarations.
PiperOrigin-RevId: 342081252
- Extend MHLO CustomCall to have multiple tensors as results.
- Extend LHLO CustomCall to have multiple memrefs for output operands.
- Fix HLO->LHLO and XLA HLO->LHLO mapping for CustomCall to setup the
operand_segment_sizes attribute correctly.
PiperOrigin-RevId: 342067762
This is to match with HLO semantics and general dimension semantics in MLIR.
Also,
* Define minimal verifier for these ops.
* Add folder for SetDimensionSize op on static shaped dimension.
* Fix assumption of ranked shape in GetDimensionSize op.
PiperOrigin-RevId: 341150923
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/44405
Splitting #43857 by top-level directories.
Copybara import of the project:
--
fa5da7d5478649d11321dcac9f867b0a57e4798a by Dmitry Volodin <mr.molkree@gmail.com>:
fix typos in compiler dir
--
4d3c9f047f7ecb8ab299f1bf28a86fd39096eee7 by Dmitry Volodin <mr.molkree@gmail.com>:
fix one test as "atleast" in it comes from Bazel
--
9440ebaaa9fc4a735f7f72f0c8f0de4ec58afbd6 by Dmitry Volodin <mr.molkree@gmail.com>:
a bit more
PiperOrigin-RevId: 340819994
The slice indices must be rank-1 and have the same number of elements of the
rank of the operand. Give reasonable error messages for violations of these
requirements instead of a misleading error message that the types of the
indices don't all match.
PiperOrigin-RevId: 340660822
XLA HLO concat does not accept scalars, so fail verification if this occurs. Avoids segfault when accessing an empty output shape.
PiperOrigin-RevId: 337618167
- Use MLIR provided constraints for HLO_ScalarIntTensor and HLO_DimensionTensor.
- Update unit tests to expect new error messages.
PiperOrigin-RevId: 333313131
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
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
mhlo.get_tuple_element supports extracting a mhlo.token type from a tuple. This updates the creation of tuples to allow for mhlo.token typed operands.
PiperOrigin-RevId: 324628663
Constants of unknown shape cannot be materialized. In most cases, one likely wants to use a scalar constant and rely on broadcasting instead.
PiperOrigin-RevId: 324252475
Also add a localized `mlir-hlo-opt` binary for the testing of
tensorflow/compiler/mlir/hlo/... ; this directory is intended to be self-contained
and depend only on MLIR.
PiperOrigin-RevId: 319878984
Jacques Pienaar
A. Unique TensorFlower
Rahul Joshi
Geoffrey Martin-Noble
Richard Uhler
Smit Hinsu
Dmitry Volodin
Tim Shen
Robert Suderman
Prakalp Srivastava
Andy Ly
Lucy Fox
Stephan Herhut
Mehdi Amini