Commit Graph

416 Commits

Author SHA1 Message Date
A. Unique TensorFlower db05388a3c Integrate LLVM at llvm/llvm-project@da3ed58b97
Updates LLVM usage to match
[da3ed58b97c1](https://github.com/llvm/llvm-project/commit/da3ed58b97c1)

PiperOrigin-RevId: 377432380
2021-06-03 20:45:18 -07:00
A. Unique TensorFlower aba16adfa5 Add `mhlo.all_gather` op to MHLO dialect.
Adds import/export/verifier support as well.
Also makes `channel_handle` uniform across mhlo.all_reduce and mhlo.all-gather.

PiperOrigin-RevId: 377323468
2021-06-03 10:45:29 -07:00
A. Unique TensorFlower 4620410f18 Integrate LLVM at llvm/llvm-project@b25546a4b4
Updates LLVM usage to match
[b25546a4b406](https://github.com/llvm/llvm-project/commit/b25546a4b406)

PiperOrigin-RevId: 377077163
2021-06-02 09:32:59 -07:00
A. Unique TensorFlower 75a1c450ea [MLIR][KernelGen] Fix Windows build failure
Fix usage of default constructor. Instead, always use the parameterized
constructor and make the maximum supported rank explicit.

PiperOrigin-RevId: 377037155
2021-06-02 05:34:44 -07:00
wyzhao 968d4b8709 PR #49598: [MLIR][DISC] legalize tensor_load inserted during hlo-to-lhlo conversion
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/49598

This PR implements logic for lowering memref.tensor_load ops that are
inserted during `mhlo-legalize-to-lmhlo`
Copybara import of the project:

--
80eb377af4e02182e1aecc943a41ca5d7d1c2100 by Wenyi Zhao <reyizero@gmail.com>:

[MLIR][DISC] legalize tensor_load inserted during hlo-to-lhlo conversion

This PR implements logic for lowering memref.tensor_load ops that are
inserted during `mhlo-legalize-to-lmhlo`.

--
ac452fe3dcd591211cd5c59be9189fe2f7153b41 by Wenyi Zhao <reyizero@gmail.com>:

minor fix

--
6b36017f8632a06adbc3e05a62975fa641d0260f by Wenyi Zhao <reyizero@gmail.com>:

minor refine

--
846005cc76d0033112e47825c2e9a97790b6925f by Wenyi Zhao <reyizero@gmail.com>:

minor fix

--
f6a4becaa287d5ca323b2d152a4d0ae053730fd9 by Wenyi Zhao <reyizero@gmail.com>:

fix

--
5555749f60f7fce8f57962860ef65efccf0362ba by Wenyi Zhao <reyizero@gmail.com>:

fix

--
8873b9b6d9315c1199ca9f7c133ecf377ecd2fa6 by Wenyi Zhao <reyizero@gmail.com>:

fix

PiperOrigin-RevId: 376942547
2021-06-01 16:27:56 -07:00
A. Unique TensorFlower d1828625ab [MLIR][KernelGen] Make maximum supported rank in rank specialization configurable
The maximum supported target rank of 5 is sufficient for all operations but
`select`. Make the maximum target rank configurable in the rank specialization.
This reduces the number of generated kernels for operations that don't require
it.

PiperOrigin-RevId: 376822496
2021-06-01 06:54:31 -07:00
A. Unique TensorFlower c7c245eaf1 [MLIR][KernelGen] Add MLIR-generated Xlogy kernel
Add the first MLIR-generated kernel that relies on an in-TF lowering. Fusion for
this kernel relies on the generalized rank specialization for operation groups.

PiperOrigin-RevId: 376805435
2021-06-01 04:48:18 -07:00
A. Unique TensorFlower f16e5a3a67 [MLIR][HLO] Use canonicalization patterns in broadcast propagation pass
Replace local canonicalization patterns with those from upstream.

PiperOrigin-RevId: 376794178
2021-06-01 03:14:31 -07:00
A. Unique TensorFlower 31536431e0 [MLIR][HLO] Eliminate duplicate broadcastable constraints
PiperOrigin-RevId: 376718433
2021-05-31 13:50:23 -07:00
A. Unique TensorFlower 0f341012c6 [MLIR][HLO] Eliminate duplicate broadcastable constraints
PiperOrigin-RevId: 376715240
2021-05-31 13:08:02 -07:00
A. Unique TensorFlower 511a1db4f3 [MLIR][HLO] Use canonicalization patterns in broadcast propagation pass
Replace local canonicalization patterns with those from upstream.

PiperOrigin-RevId: 376708719
2021-05-31 12:01:26 -07:00
A. Unique TensorFlower 5f5db13715 [MLIR][HLO] Use canonicalization patterns in broadcast propagation pass
Replace local canonicalization patterns with those from upstream.

PiperOrigin-RevId: 376707588
2021-05-31 11:44:50 -07:00
A. Unique TensorFlower cc1b22e618 [HLO][Linalg] Support scalar broadcasts in point-wise converter
This is needed for operations that support this limited form of broadcasting,
namely `mhlo.select`.

PiperOrigin-RevId: 376655844
2021-05-31 03:50:23 -07:00
Hanhan Wang 402b74ed7f Fix type bug in mhlo.dynamic-update-slice lowering.
The operand type can be f32. We should not use operand type to do clamp
operations.

PiperOrigin-RevId: 376286524
2021-05-27 17:53:49 -07:00
Adrian Kuegel a4fa6afa07 [mlir][hlo] Avoid dyn_cast_or_null when called with getDefiningOp result (NFC)
PiperOrigin-RevId: 376110457
2021-05-27 00:20:42 -07:00
Hanhan Wang 28c411606f Add support for lowering mhlo.dynamic-update-slice ops to Linalg and std ops.
PiperOrigin-RevId: 376042810
2021-05-26 15:31:05 -07:00
Robert Suderman 26a0053d7d Remove linalg.indexed_generic from mhlo lowerings to linalg
IndexedGeneric is going away. Transition to using linalg.Index instead.

PiperOrigin-RevId: 376002501
2021-05-26 12:24:23 -07:00
A. Unique TensorFlower 4ebcebf31c [MLIR][HLO] Exploit scalar properties in rank specialization lowering
Take advantage of the fact that scalars are already ranked and that they are
neutral elements to broadcasting. Do not reshape scalars, do not consider them
for broadcasting, and materialize ranked operations on scalars accordingly.

PiperOrigin-RevId: 375968371
2021-05-26 09:59:13 -07:00
A. Unique TensorFlower cb46298a07 [MLIR][HLO] Support all smaller ranks in rank specialization cases
Rank specialization cases can be applied to all argument tensors of smaller
ranks than the expected maximum rank. This is crucial if all operands are
effectively scalars and the maximum reduced rank is 0.

PiperOrigin-RevId: 375712020
2021-05-25 08:38:53 -07:00
wyzhao b93e54d8a4 PR #49454: [MLIR][DISC] Upgrade to use the new `reifyReturnTypeShapes` interface.
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/49454

The new interface is more safe to be used during dialect conversion
(e.g. converting from tensor world to buffer world).
Copybara import of the project:

--
a6968072d59bec3c3bbaef0121d297e807c37c91 by Wenyi Zhao <reyizero@gmail.com>:

[MLIR][DISC] Upgrade to use the new `reifyReturnTypeShapes` interface.

The new interface is more safe to be used during dialect conversion
(e.g. converting from tensor world to buffer world).

--
55e7c6b7f2f99b99e226645a57e2433fae3e90ed by Wenyi Zhao <reyizero@gmail.com>:

minor fix

PiperOrigin-RevId: 375500273
2021-05-24 10:11:55 -07:00
Stella Laurenzo 28c4112f35 Downgrade some emitErrors in patterns to notifyMatchFailure.
PiperOrigin-RevId: 375160543
2021-05-21 14:09:23 -07:00
Hanhan Wang 1ba4c714c9 Add support for lowering mhlo.scatter ops to Linalg.
This only works for updating tensors, not add/min/max computations. It requires
the index depth to be 1 because of the limitation in Linalg. We can not compare
multiple indices without packing indices.

PiperOrigin-RevId: 375137721
2021-05-21 12:17:14 -07:00
A. Unique TensorFlower 97e6103933 [MLIR][HLO] Reshape to scalars in rank specialization
Scalars were incorrectly casted to scalar tensors when they have to be reshaped.

PiperOrigin-RevId: 375049088
2021-05-21 03:12:16 -07:00
A. Unique TensorFlower 3daf65578a [MLIR][HLO] Add scalar cases for binary rank specialization
For rank specialization clusters that have only two operands, we can materialize
two extra cases in which either of them is a scalar. This avoids redundant index
computations in these cases.

PiperOrigin-RevId: 375037390
2021-05-21 01:35:44 -07:00
Feiwen a7884196f5 PR #49228: [MLIR][DISC] porting dynamic shape related OPs to mhlo and lmhlo dialect
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/49228

We are porting our MLIR-based dynamic shape compiler to tf community (From OP def, Patttern, to Optimization pass, etc).
This is the first PR, which including some dynamic shape OPs def in mhlo and lmhlo dialect.
For mhlo dialect, we add:
- HLO_RealDynamicSliceOp
- HLO_DynamicPadOp
- HLO_DynamicGatherOp
- HLO_DynamicConvOp

For lmhlo dialect, we add:
- LHLO_RealDynamicSliceOp
- LHLO_DynamicBroadcastInDimOp
- LHLO_DynamicGatherOp
- LHLO_DynamicPadOp
- LHLO_DynamicBitcastOp
- LHLO_DynamicConvOp
- LHLO_DynamicIotaOp
- LHLO_DynamicReshapeOp
- LHLO_DotGeneralOp
- LHLO_BitcastOp

Rest Ops to add:
* We will send a separate PR containing LHLO_DynamicWhileOp and LHLO_DynamicCaseOp for control flow.
* We will add a separate dedicated dialect like mhlo_ral, which including D2HOp/H2DOp/DebugPrintOp/TopKOp, etc.

Previous discussions:[RFC](https://groups.google.com/a/tensorflow.org/g/mlir/c/_X48poNcbDI/m/jCC8BWIICQAJ), [discussion_1](https://llvm.discourse.group/t/updates-on-mlir-based-dynamic-shape-compiler/2384), [Recording of meeting](https://drive.google.com/file/d/1_uEISlV5MUWdG9faKAdKlCWnPtGjRC-D/view?usp=sharing).
Copybara import of the project:

--
e22d9e61106e00a1a1c6f368cc4a03e3bd1f414c by azazhu <azazhu@gmail.com>:

[DISC]fea: porting mhlo and lmhlo OPs

--
9ec3e76290da07cbd53d7da5fa86ff67179441a1 by azazhu <azazhu@gmail.com>:

[DISC][MLIR] 1. add summary and description for dynamic OPs in mhlo and lmhlo; 2. rm InferOutputTypes; 3. add verify for RealDynamicSliceOp and DynamicPadOp

--
0d68cd135555fd935991c12456b21329e628f23f by azazhu <azazhu@gmail.com>:

[DISC][MLIR] 1.remove D2H,H2D and DebugPrint Ops from mhlo/lmhlo dialect; 2. add type constraint to DynamicPadOp and RealDynamicSliceOp; 3.refine lmhlo type constraint; 4.rename RealDynamicSliceOp as name conflict.

--
698762a77d60f6a844cb1ab3f32740d4ef3c5843 by azazhu <azazhu@gmail.com>:

[DISC][MLIR] 1. replace dyn_cast to cast 2. refine code

PiperOrigin-RevId: 375022260
2021-05-20 23:16:47 -07:00
Hanhan Wang cd8f585cf7 [MHLO:Linalg] Add support for lowering torch_index_select of unsigned tensors
Also fixes typos in tests.

PiperOrigin-RevId: 374979460
2021-05-20 17:03:05 -07:00
Rahul Joshi 41f663ce47 [HLO] Adopt custom syntax for convolution dimensions and window attributes (HLO)
PiperOrigin-RevId: 374923250
2021-05-20 12:13:50 -07:00
Rahul Joshi fc88cf1ff4 [HLO] Adopt custom syntax for convolution dims and window attributes for LMHLO_GPU
PiperOrigin-RevId: 374889917
2021-05-20 09:41:48 -07:00
A. Unique TensorFlower 57aeb5ab16 Integrate LLVM at llvm/llvm-project@0316f3e649
Updates LLVM usage to match
[0316f3e64972](https://github.com/llvm/llvm-project/commit/0316f3e64972)

PiperOrigin-RevId: 374855085
2021-05-20 06:09:40 -07:00
A. Unique TensorFlower c62fd89663 [MLIR][HLO] Add equal shapes case to rank specialization
Also restructure lowering implementation to facilitate the addition or removal
of special cases.

PiperOrigin-RevId: 374626365
2021-05-19 05:38:42 -07:00
Stella Laurenzo 71394fb301 Properly handle if DynamicBroadcastInDimOp shape is not of index type.
* The op defines this to be index, any integer, or pred (i1).
* Many TensorFlow legalizations produce integers for the shape.

PiperOrigin-RevId: 374566113
2021-05-18 21:12:11 -07:00
Stella Laurenzo 0fe07e3814 Separate CHLO transforms for expanding compositions and lowering broadcasts.
* The former is typically invariant regardless of backend.
* The latter may need to be done differently depending on capabilities of the lowering target.

PiperOrigin-RevId: 374492924
2021-05-18 13:33:59 -07:00
A. Unique TensorFlower 6af3d2df91 [MLIR][HLO] Add rank specialization with multiple non-scalar operands
Add lowering pattern for rank specialization clusters with more than one
non-scalar operand. The lowering resembles that of the `TransformUnrankedHlo`
pass and switches cases for maximal ranks from 1 through 8.

PiperOrigin-RevId: 374377002
2021-05-18 03:02:45 -07:00
A. Unique TensorFlower 474e419729 [MLIR][HLO] Generalize rank specialization with single operand
The pattern can be generalized to also rank specialize operations with a single
non-scalar operand. Also extract helper functions that can be reused in
following specializations.

PiperOrigin-RevId: 374198381
2021-05-17 08:12:55 -07:00
A. Unique TensorFlower c514c73390 [MLIR][HLO] Extend rank specialization clustering pass
Also cluster operations that operate on same shape operands. These implicitly
satisfy the broadcasting semantics requirement. Also, add test cases for some
cases that appear in the current MLIR-generated kernels.

PiperOrigin-RevId: 374191950
2021-05-17 07:31:36 -07:00
A. Unique TensorFlower ccd70d5717 [MLIR][HLO] Add `rank-specialization-to-scf` pass
Currently the lowering is only implemented for the unary case. The n-ary case
will follow.

PiperOrigin-RevId: 374162772
2021-05-17 03:56:23 -07:00
Ben Vanik b06baae910 Fixing nondeterminism in pattern application.
The ReduceRegion* patterns are matching on the same ops as the PointwiseToLinalg*
patterns and on certain toolchains (MSVC) the order can be wrong. If the pointwise
runs first then it converts the op *within* the reduction before the reduction one
runs, leading to nested linalg op weirdness.

PiperOrigin-RevId: 373848269
2021-05-14 12:57:39 -07:00
Rahul Joshi a361253e4f [HLO] Add custom print/parse for window attributes of convolutions (in LMHLO)
PiperOrigin-RevId: 373807616
2021-05-14 09:47:25 -07:00
A. Unique TensorFlower d2cc74317c Implement constant folding for mhlo.Sign.
PiperOrigin-RevId: 373550014
2021-05-13 03:54:04 -07:00
Hanhan Wang d764806c1e [MHLO:Linalg] Add support for lowering reshape of unsigned tensors
PiperOrigin-RevId: 373461627
2021-05-12 15:14:29 -07:00
A. Unique TensorFlower 420c42a0a1 [MLIR][HLO] Support CHLO unary operations in rank specialization clustering
PiperOrigin-RevId: 373397321
2021-05-12 10:20:43 -07:00
Rahul Joshi e260aa771c [HLO] Add custom print/parse for convolution dimension numbers (in LMHLO)
PiperOrigin-RevId: 373379227
2021-05-12 08:52:46 -07:00
A. Unique TensorFlower 313d24bc8f [MLIR][HLO] Add `rank-specialization-cluster` pass
Add a pass to cluster unranked C/HLO operations in one
`chlo.rank_specialization_cluster` op. The C/HLO operations are moved to the
body of the operation. Later passes can use this to rank-specialize all these
operations together.

PiperOrigin-RevId: 373336725
2021-05-12 03:46:01 -07:00
A. Unique TensorFlower 7f7a86ad0d [MLIR][HLO] Implement `RegionBranchOpInterface` for rank specialization cluster
PiperOrigin-RevId: 373163196
2021-05-11 09:03:05 -07:00
A. Unique TensorFlower 96a47345cc [MLIR][HLO] Add `rank_specialization_cluster` op to CHLO
The operation will be used to cluster compatible operations that can be rank-
specialized collectively.

PiperOrigin-RevId: 373128557
2021-05-11 05:17:42 -07:00
Benjamin Kramer 86b7eb434c [MHLO] Don't crash trying to constant fold mhlo.convert on complex
MLIR still doesn't have a complex attribute so this can't be implemented, so
just bail out instead of trying to fold.

PiperOrigin-RevId: 373128307
2021-05-11 05:15:57 -07:00
A. Unique TensorFlower 7f86dd9f7e Constant fold compare EQ if one of the operands is true and compare NE if one of the operands is false.
PiperOrigin-RevId: 373058030
2021-05-10 18:53:49 -07:00
A. Unique TensorFlower d8c40b691c [MLIR][HLO] Add `shape.broadcast` canonicalization to unblock broadcast moving
PiperOrigin-RevId: 372120309
2021-05-05 07:16:49 -07:00
dfki-jugr 6bc854f5d9 PR #48667: [mlir-hlo] Added RegionBranchOpInterfaces to lmhlo operations.
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/48667

Added RegionBranchOpInterfaces to lmhlo operations that use regions.
This is needed, since the bufferization features in MLIR have to reason about the control flow within these operations.
Copybara import of the project:

--
572fd7d850a46630b812da84e9094280f89f259e by Julian Gross <julian.gross@dfki.de>:

Added RegionBranchOpInterfaces to lmhlo operations.

PiperOrigin-RevId: 372070825
2021-05-05 00:27:56 -07:00
Geoffrey Martin-Noble ac68145565 [MHLO:Linalg] Add support for lowering concat of unsigned tensors
Nothing about concat here really. Just need to plumb through the type
conversion.

PiperOrigin-RevId: 372012957
2021-05-04 15:57:54 -07:00