Commit Graph

164 Commits

Author SHA1 Message Date
Stephan Herhut 70a351f301 Add chlo.acosh operation and associated lowerings.
PiperOrigin-RevId: 352839289
2021-01-20 11:43:44 -08:00
Tres Popp ba0346b071 Integrate LLVM at llvm/llvm-project@96ef4f307d
Updates LLVM usage to match
[96ef4f307df2](https://github.com/llvm/llvm-project/commit/96ef4f307df2)

PiperOrigin-RevId: 352786460
2021-01-20 07:09:47 -08:00
A. Unique TensorFlower ec5f5667e1 [MLIR][KernelGen] Add `tf.Asinh` kernels and complete their lowerings
PiperOrigin-RevId: 352773540
2021-01-20 05:31:15 -08:00
A. Unique TensorFlower 96fb617413 [MLIR][KernelGen] Add erf kernel and missing lowering for f16 type
PiperOrigin-RevId: 352416184
2021-01-18 08:21:15 -08:00
Tres Popp ba2ee556f1 Handle negative exponents for lowering of hlo.pow
PiperOrigin-RevId: 352382812
2021-01-18 03:47:28 -08:00
A. Unique TensorFlower 3763740910 [MLIR][KernelGen] Add erf kernel for f32 arguments and missing lowerings
PiperOrigin-RevId: 352381016
2021-01-18 03:35:13 -08:00
A. Unique TensorFlower bcdb3c3548 [MLIR] Lower mhlo.clamp to linalg
PiperOrigin-RevId: 351998800
2021-01-15 06:45:38 -08:00
A. Unique TensorFlower 9a1abaa212 Integrate LLVM at llvm/llvm-project@e2d7d3cb0e
Updates LLVM usage to match
[e2d7d3cb0ead](https://github.com/llvm/llvm-project/commit/e2d7d3cb0ead)

PiperOrigin-RevId: 351915841
2021-01-14 18:05:33 -08:00
Hanhan Wang 300a7c11ce Upstream mhlo.dot_general lowering to Linalg to MHLO repo
PiperOrigin-RevId: 351514250
2021-01-12 22:08:46 -08:00
Hanhan Wang 8f58f844e5 Upstream mhlo.dot lowering to Linalg to MHLO repo.
We prototyped the lowering from mhlo.dot to linalg.matmul in IREE. Since Linalg
now supports matmul in tensors world, we can move the lowering logic to tensors
world, and upstream to legalize_to_linalg.cc. The patch lowers the mhlo.dot to
the linalg.matmul/matvec/dot in tensors world.

PiperOrigin-RevId: 351184911
2021-01-11 10:35:24 -08:00
Alexander Belyaev 180f917446 [KERNEL_GEN] Add a pattern for hlo.dyn_broadcast->linalg to enable is_inf kernel.
PiperOrigin-RevId: 351179620
2021-01-11 10:13:31 -08:00
Alexander Belyaev ecf1bf5132 [KERNEL_GEN] Add a canonicalization pattern to drop a redundant dynamic reshape.
PiperOrigin-RevId: 351141868
2021-01-11 06:38:03 -08:00
Alexander Belyaev 6c42f54298 [KERNEL_GEN] Restrict broadcast -> reshape canonicalization to identity dims.
This is needed to avoid the case, when the broadcast_in_dims also performs permutation.

PiperOrigin-RevId: 350650342
2021-01-07 15:30:28 -08:00
Alexander Belyaev 095dc28e5c [KERNEL_GEN] Add canonicalizaton pattern to drop a redundant broadcast op.
PiperOrigin-RevId: 350105790
2021-01-05 03:01:00 -08:00
A. Unique TensorFlower b0bf2ef45b Integrate LLVM at llvm/llvm-project@c3acda0798
Updates LLVM usage to match
[c3acda0798f9](https://github.com/llvm/llvm-project/commit/c3acda0798f9)

PiperOrigin-RevId: 348896724
2020-12-23 23:53:54 -08:00
Stephan Herhut ccdd07f8e4 Prepare to remove tensor_load and tensor_store special handling from hlo to lhlo legalization.
This updates the tests to no longer rely on tensor_store. Once all users of this behavior have adopted, the tensor_store support will be removed.

PiperOrigin-RevId: 348624899
2020-12-22 06:29:12 -08:00
Tres Popp a42213b870 Define lowering of [l]mhlo.pow.
For floating point operations, this uses std.pow.
For integer operations, this lowers to a loop.
This adds a dependency on scf.

PiperOrigin-RevId: 348537232
2020-12-21 15:27:40 -08:00
Smit Hinsu 737d15ded5 Handle operands with zero elements in HLO PadOp folder
PiperOrigin-RevId: 348034821
2020-12-17 09:27:36 -08:00
Rahul Joshi 8134bff98d [XLA:GPU] Add layout attributes to LHLO_GPU Convolution operations.
- MLIR MemRefs do not preserve layout information correctly when unit dimensions
  are involved. Operations like convolution that use cuDNN however need the correct
  layout to be preserved so that we do not end up creating an incompatible combination
  of input/filter/output layout that is not supported by cuDNN.
- Add these layouts to convolution attributes in the form of I32ArrayAttr for representing
  the layout in "minor_to_major" form similar to XLA.

PiperOrigin-RevId: 348034757
2020-12-17 09:26:28 -08:00
Adrian Kuegel 1f244c3e2c Fix SignOp lowering for floating point values.
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.

PiperOrigin-RevId: 347981124
2020-12-17 01:45:54 -08:00
A. Unique TensorFlower 5da9190dd9 Integrate LLVM at llvm/llvm-project@0cf7e4b252
Updates LLVM usage to match
[0cf7e4b252fe](https://github.com/llvm/llvm-project/commit/0cf7e4b252fe)

PiperOrigin-RevId: 347948887
2020-12-16 20:30:17 -08:00
Alexander Belyaev 65222893ae [KERNEL_GEN] Convert LHLO AddOp, SubOp (ComplexType) to complex ops.
PiperOrigin-RevId: 347805898
2020-12-16 05:45:06 -08:00
Alexander Belyaev e6e8920921 [KERNEL_GEN] Switch the pipeline to Linalg-on-Tensors.
PiperOrigin-RevId: 347781190
2020-12-16 01:51:15 -08:00
A. Unique TensorFlower f0c2695d31 Fix SignOp lowering for floating point values.
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.

PiperOrigin-RevId: 347602378
2020-12-15 06:49:48 -08:00
Alexander Belyaev ddda2699fb [KERNEL_GEN] Switch the pipeline to Linalg-on-Tensors.
PiperOrigin-RevId: 347600145
2020-12-15 06:32:25 -08:00
Adrian Kuegel 79fa36bcbc Fix SignOp lowering for floating point values.
It didn't return 0 for 0.0 and -0.0.
Currently we emit -0.0 for -0.0 which is correct according to the HLO dialect.
For the TF_SignOp we should emit 0.0 in that case, we will leave that as a TODO.
Enable the tests which work now, and add another one for Int64.
Also improve the registration code, we should not register the Int32 kernel.

PiperOrigin-RevId: 347590340
2020-12-15 05:12:48 -08:00
Alexander Belyaev 8b35a75d4a [KERNEL_GEN] Switch the pipeline to Linalg-on-Tensors.
PiperOrigin-RevId: 347368063
2020-12-14 05:46:47 -08:00
Benjamin Kramer 9930c20c31 [mlir][hlo] Fix lowering of NE comparison. It should return true if either side is NaN
PiperOrigin-RevId: 346988987
2020-12-11 06:46:14 -08:00
Smit Hinsu ab6ee11813 Fix folding of HLO SliceOp with zero elements
This was causing division by zero in this case.

PiperOrigin-RevId: 346920942
2020-12-10 20:22:48 -08:00
Rahul Joshi f232da1f9d [MLIR:HLO] Add window_reversal attribute to convolution attributes.
- Add this attribute to match the corresponding XLA HLO attribute on convolution
  operations.
- A true value indicates a reversal of the corresponding kernel spatial dimension.
- Since XLA builder does not support this attribute, use a custom HLO converted to map
  from mlir::mhlo::ConvOp to XLA.

PiperOrigin-RevId: 346891737
2020-12-10 16:39:19 -08:00
Alexander Belyaev c36afd275e [HLO] Add a pattern for HLO ConstOp to HLO -> Linalg conversion.
PiperOrigin-RevId: 346718273
2020-12-09 23:24:57 -08:00
Stephan Herhut c3790af758 Add plumbing for or and xor to hlo to lhlo and linalg lowerings.
PiperOrigin-RevId: 346311314
2020-12-08 06:39:02 -08:00
Benjamin Kramer 5235eceea0 Lower mhlo shifts to linalg
PiperOrigin-RevId: 346161253
2020-12-07 13:02:32 -08:00
Tres Popp d327fc5737 [kernel_gen] Lower max rank specialization from 6 to 5
We don't care much about rank 6 broadcasting operations and this lowers compile times significantly.

PiperOrigin-RevId: 346046601
2020-12-07 02:18:38 -08:00
Phoenix Meadowlark c33bdcbd03 Remove fold of `mhlo.compare(%arg0, %arg0)` for floating types.
Two tensors having the same SSA-value isn't sufficient for equality for floating types, as `NaN != NaN`. As written this causes `tf.IsNan` to [miscompile](https://github.com/google/iree/issues/4061).

PiperOrigin-RevId: 345730640
2020-12-04 12:15:02 -08:00
Rahul Joshi e48881af81 [MLIR:LHLO_GPU] Add fused convolution operation without any side inputs.
- Add a variant of the fused convolution that does not need a side input and side input scale.
- Rename the existing one to `ConvForwardFusedSideInputOp`.
- Update tests to exercise all variants of the convolution ops in the GPU dialect.
- Eliminate unused `LHLO_ExtentBuffer` and changed LHLO_Buffer to allow any integer element
  type to match what XLA can generate sometimes for scratch buffers.

PiperOrigin-RevId: 345701569
2020-12-04 10:09:27 -08:00
Tres Popp 7c3f049c8e [kernel_gen] Lower max rank specialization from 6 to 5
We don't care much about rank 6 broadcasting operations and this lowers compile times significantly.

PiperOrigin-RevId: 345466476
2020-12-03 09:19:25 -08:00
Rahul Joshi d7bd5233ab [XLA:GPU] Migrate GEMM Thunk emission to MLIR.
- Map Custom call for GEMM in XLA HLO to Gemm/Gemm bias operations in LHLO GPU
  dialect.
- Make 'algorithm' an optional attribute to better match with XLA HLO backend config.
- Replace 'alpha' with 'alpha_real' and 'alpha_complex' to support complex GEMM correctly.
- Generate GemmThunk off of LHLO GPU Gemm operations.

PiperOrigin-RevId: 345250840
2020-12-02 09:43:12 -08:00
Adrian Kuegel d14c63da54 Add a canonicalization pattern to remove redundant dynamic_reshapes.
PiperOrigin-RevId: 344517381
2020-11-27 04:46:50 -08:00
Adrian Kuegel 6a71a84302 Support different input/output type for TransformUnrankedHlo.
Also generate the tf.Equal kernel, now that it works.

PiperOrigin-RevId: 344402014
2020-11-26 04:20:34 -08:00
Alexander Belyaev 5583c63cab [KERNEL_GEN] Add unranked Conj kernel.
PiperOrigin-RevId: 344243271
2020-11-25 06:37:26 -08:00
Smit Hinsu b016b5a219 Fix constant folding of mhlo.convert op with i1 element types
Boolean element values should be fetched as an unsigned integer and not signed integer which would return -1 for true.

Added to a TODO to handle unsigned types correctly as well as we don't seem to be using unsigned types.

PiperOrigin-RevId: 343927564
2020-11-23 14:18:28 -08:00
Rahul Joshi ac54c5ccfa [XLA:GPU] Convert Cholesky custom call in XLA HLO to LHLO GPU Dialect.
- Restructured LHLO GPU Cholesky to better match XLA HLO by eliminating the
  untyped buffer and changing is_upper attribute to is_lower.
- Change LhloDialectEmitter to emit LHLO GPU Cholesky operation.

PiperOrigin-RevId: 343873516
2020-11-23 10:06:21 -08:00
A. Unique TensorFlower 7f239c7ba2 Add canonicalizer for Reshape(Broadcast(X)) pattern when it is an identity sequence
PiperOrigin-RevId: 343251257
2020-11-19 02:32:45 -08:00
Stephan Herhut 0c7152e65c Extend fusion root heuristic to also work in partially bufferized programs.
We now follow data flow though tensor_cast, tensor_load and tensor_to_memref
operations.

PiperOrigin-RevId: 342851104
2020-11-17 06:34:48 -08:00
Tres Popp be9ae88eaa Consider aliases through control flow for lhlo-fuse-linalg.
This should handle scf.if and shape.assuming regions,
which we care about in kernel_gen.

PiperOrigin-RevId: 342584762
2020-11-16 01:12:45 -08:00
Stephan Herhut c344695bca Properly configure patterns in hlo to lhlo conversion with typeconverter.
Otherwise, materializations for partial conversions do not work.

PiperOrigin-RevId: 342215962
2020-11-13 00:58:51 -08:00
Rahul Joshi bbaad416a1 [MLIR] Update tests to eliminate public function declarations.
- 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
2020-11-12 10:42:59 -08:00
Rahul Joshi 1958f228ec [MLIR:HLO] Extend CustomCall to support multiple outputs.
- 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
2020-11-12 09:46:25 -08:00
Tres Popp 1dffa62fe9 Fold away shape.shape_of(mhlo.dynamic_reshape(inp, shape))
This specific pattern can be replaced with the shape
passed to dynamic_reshape. This is implemented as a
canonicalization on mhlo.dynamic_reshape to fit in
the infrastructure of canonicalization.

PiperOrigin-RevId: 342009365
2020-11-12 02:48:26 -08:00