Commit Graph

25 Commits

Author SHA1 Message Date
Uday Bondhugula 282dba6d38 PR #42508: [MLIR] Erase dead lmhlo.constant ops
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:

--
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
2020-08-23 12:28:54 -07:00
Jacques Pienaar 5dac76f4af Add chlo.constant_like op which splats a constant to shape of operand
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
2020-08-11 14:54:48 -07:00
A. Unique TensorFlower e6fa003bf2 Integrate LLVM at llvm/llvm-project@b6d9add71b
Updates LLVM usage to match
[b6d9add71b1a](https://github.com/llvm/llvm-project/commit/b6d9add71b1a)

PiperOrigin-RevId: 325589103
2020-08-08 04:35:25 -07:00
Andy Ly 53fdda7f3e Update mhlo.constant to use a custom assembly format instead of a custom printer and parser (NFC).
PiperOrigin-RevId: 325560779
2020-08-07 22:23:06 -07:00
Lucy Fox d742477c02 Verify that MHLO DynamicUpdateSlice start indices have matching element types.
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
2020-08-07 22:21:40 -07:00
Lucy Fox cd22ecd136 Relax DynamicBroadcastInDim verifier when dimensions are dynamic.
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
2020-08-07 22:18:38 -07:00
A. Unique TensorFlower a68a16cdc7 [MLIR][XLA] Allow for choice of safe/unsafe variant in broadcast utils
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
2020-08-07 22:16:11 -07:00
Mehdi Amini 701312720c Add CMake files and lit configurations, enough for `ninja check-mlir-hlo` to pass on all the tests
PiperOrigin-RevId: 325172984
2020-08-07 22:14:34 -07:00
Andy Ly c340367702 Add canonicalization for unpacking and repacking the same tuple (e.g. tuple -> get_tuple_element -> tuple).
These unpacking and repacking of tuples may be generated when modifying tuple arguments or results.

PiperOrigin-RevId: 325162694
2020-08-05 21:38:02 -07:00
A. Unique TensorFlower 4372124362 [MLIR][XLA] Allow for choice of safe/unsafe variant in broadcast utils
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
2020-08-05 12:43:29 -07:00
A. Unique TensorFlower 37c36a4389 [MLIR][XLA] Allow for choice of safe/unsafe variant in broadcast utils
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
2020-08-05 11:09:23 -07:00
Mehdi Amini cd01bb4c4e More cleanup in mlir-hlo to prepare for the standalone build
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
2020-08-03 19:28:00 -07:00
Thomas Joerg 739758f9cc Integrate LLVM at llvm/llvm-project@eed333149d
Updates LLVM usage to match
[eed333149d17](https://github.com/llvm/llvm-project/commit/eed333149d17)

PiperOrigin-RevId: 323354988
2020-08-03 19:27:25 -07:00
Tres Popp 63d62b7952 Change cast to dyn_cast in hlo::ReshapeOp's verification.
With cast, a failing verification results in an assertion error rather than returning a failing status.

PiperOrigin-RevId: 322317937
2020-07-30 22:34:36 +00:00
Stephan Herhut 7a6adc6a84 Add canonicalization patterns for dynamic_broadcast_in_dim where the target shape is the shape of the operand.
PiperOrigin-RevId: 321312182
2020-07-30 22:34:06 +00:00
Robert Suderman 06ae59074f Fold xla iota across a 1-length dimension into a zero value
Iota across length-1 is just a constant. Fold into it.

PiperOrigin-RevId: 320443468
2020-07-30 22:33:43 +00:00
Uday Bondhugula de0578b4f9 PR #40745: [MLIR] Add constant folder for xla_hlo.broadcast_in_dim op
Imported from GitHub PR https://github.com/tensorflow/tensorflow/pull/40745

Fold broadcast_in_dim op if the operand is the result of a tensor splat.
Copybara import of the project:

--
26c9f631448b8d6ffd20ece39ea8d4132b5550c7 by Uday Bondhugula <uday@polymagelabs.com>:

[MLIR] Add constant folder for xla_hlo.broadcast_in_dim op

Fold broadcast_in_dim op if the operand is the result of a tensor
splat.

COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/tensorflow/pull/40745 from polymage-labs:broadcast_in_dim_fold 26c9f631448b8d6ffd20ece39ea8d4132b5550c7
PiperOrigin-RevId: 320365164
2020-07-30 22:33:34 +00:00
Mehdi Amini 506ddd9c4a Cleanup build rule names in compiler/mlir/hlo to remove the redundant/obsolete xla_ prefix
PiperOrigin-RevId: 320320140
2020-07-30 22:33:29 +00:00
Mehdi Amini a575636862 Rename XlaHloDialect class into MhloDialect following the recent dialect namespace renaming
PiperOrigin-RevId: 320213526
2020-07-30 22:33:20 +00:00
Mehdi Amini 94dcb90d38 Rename xla_chlo dialect into chlo
Following on the plan of isolating the compiler/mlir/hlo directory.

PiperOrigin-RevId: 320212018
2020-07-30 22:33:16 +00:00
Mehdi Amini 7c4a5d62b5 Rename xla_lhlo dialect into lmhlo
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
2020-07-30 22:33:11 +00:00
Robert Suderman e1651b6090 Canonicalize multidimensional iota to use broadcast
There is no reason to have a multidimensional iota for codegen.
This should be canonicalized to a single dimensional iota followed
by a broadcast. Changing iota to on a single dimension  and a broadcast
substantially simplifies implementing iota operations.

PiperOrigin-RevId: 320095470
2020-07-30 22:32:54 +00:00
Mehdi Amini 8900222fed Rename `xla_hlo` dialect to `mhlo`
This is part of the current refactoring of the HLO related dialect.
`xla_hlo` will be reintroduced in a new form later.

PiperOrigin-RevId: 319916753
2020-07-30 22:32:50 +00:00
Alexander Belyaev 72010faaa7 [MLIR][LHLO] Add ReshapeMemrefCastOp to LHLO.
PiperOrigin-RevId: 319799171
2020-07-30 22:32:36 +00:00
Mehdi Amini fcf3df1541 Move the HLO/LHLO dialects to a new directory: tensorflow/compiler/mlir/hlo
We're preparing to restructure the MLIR HLO ecosystem with 5 dialects:

- chlo: client dialect with explicit broadcast and multiple composite operations
- mhlo: hlo with dynamic shape, decouple from XLA for evolution purpose
- lmhlo: same as above, but after buffer assignment.
- xla_hlo: mapping 1:1 to the XLA HloInstruction class.
- xla_lhlo: same as above, but after buffer assignment.

The first three dialects are intended to live in the new tensorflow/compiler/mlir/hlo
path, the latter two will be created in tensorflow/compiler/mlir/xla.

This patch only moves the directory, will followup with other transformations and tests.

The structure of the new directory follows: https://llvm.discourse.group/t/rfc-canonical-file-paths-to-dialects/621 as we intend to make it a standalone buildable component (see also https://github.com/google/mlir-npcomp as another example).

PiperOrigin-RevId: 319273229
2020-07-30 22:32:32 +00:00